Digital Commons Network^™

The Medium-Term And Event-Scale Tropical Cyclone-Driven Morphodynamics Of A Vulnerable Barrier System With Emphasis On The Role Of Backbarrier Wetlands, Cody Lee Johnson I

LSU Doctoral Dissertations

Coastal mainland barriers and barrier islands provide the first line of defense against oceanic and meteorological forces. Coastal morphological change, which may degrade these barrier's defensive capabilities, occurs over a range of time scales, from geological epochs (>1000 years) to hours and seconds. Coastal morphological change at a vulnerable, but economically strategic, barrier system---the Caminada-Moreau Headlands, Louisiana---is investigated in terms of tropical cyclone impacts and their effects over a 15 year LIDAR survey time series. Analysis of the barrier's three-dimensional morphodynamics at medium-term (decadal) time scales reveals that, while subaerial volume was approximately conserved through time, the impact of …

Characterization Of Shallow Subsurface Hydrology In Large Fine-Grained Floodplains, Mary Grace Lemon

LSU Doctoral Dissertations

Floodplains are hydrologically dynamic, receiving water from overbank events, hyporheic flows, local precipitation, and regional groundwater sources. These sources are variously important contributors to the heterogeneous floodplain water pool that includes matrix water in soil micropores, mobile water in soil macropores, groundwater below the rooting zone, ephemeral to seasonal surface storage, and permanent surface water features such as oxbow lakes, sloughs, and other secondary channels. All sources may be ecologically relevant for floodplain vegetation, but the exact roles of each source in both controlling soil water and shallow groundwater recharge and in controlling floodplain water drainage are not well understood, …

Southwest Pacific Tropical Cyclone Frequency And Intensity Related To Observed And Modeled Geophysical And Aerosol Variables, Rupsa Bhowmick

LSU Doctoral Dissertations

The dissertation focuses on western region of Southwest Pacific Ocean (SWPO)

basin (135E - 180, and 5S - 35S) tropical cyclone (TC) climatology using observed

and modeled data. The classification-based machine learning approach

identifies the synoptic geophysical and aerosol environment favorable or unfavorable

for TC intensification and intensity change prior to landfall incorporating

observational and satellite data. A multiple poisson regression model with varying

temporal monthly lags was used to build a relationship between the number of

monthly TC days with basin wide average dust aerosol optical depth (AOD), sea

surface temperature (SST), and upper ocean temperature (UOT). This idea …

Quantum Criticality In Strongly Correlated Electron Systems, Samuel Obadiah Kellar

LSU Doctoral Dissertations

The study of the Hubbard model in three dimensions contains a variety of phases dependent upon the chosen parameters. This thesis shows that there is the indication of a zero temperature phase transition at a finite doping. The Hubbard model has been used to identify a similar quantum critical point in two dimensions. The presented results continue these investigations. The system demonstrates a strange metal phase at finite temperature which cannot be described in term of the conventional Fermi liquid. While there have been extensive studies over the past three decades for such materials in two dimensions, there are few …

Insights To Gray Seal (Halichoerus Grypus) Foraging Ecology From Stable Isotope And Dna Metabarcoding Analyses, Keith Michael Hernandez

LSU Doctoral Dissertations

The enactment of wide-ranging conservation laws in the United States enabled the recovery of many marine mammal species. However, as many species have surpassed predicted recovery goals, there is an increasing number of marine mammal-human interactions. For example, in the northeast US, the recovery of gray seals (Halichoerus grypus atlantica), coupled with declines in commercially important fishery species, has prompted discussions of revised management, and potentially lethal control measures. Much of this concern stems from seal-fisheries interactions, which necessitates an understanding of seal diets and foraging ecology. However, existing research is out of date and reliant primarily on …

Identifying Structure Transitions Using Machine Learning Methods, Nicholas Walker

LSU Doctoral Dissertations

Methodologies from data science and machine learning, both new and old, provide an exciting opportunity to investigate physical systems using extremely expressive statistical modeling techniques. Physical transitions are of particular interest, as they are accompanied by pattern changes in the configurations of the systems. Detecting and characterizing pattern changes in data happens to be a particular strength of statistical modeling in data science, especially with the highly expressive and flexible neural network models that have become increasingly computationally accessible in recent years through performance improvements in both hardware and algorithmic implementations. Conceptually, the machine learning approach can be regarded as …

Antimicrobial Strategies For Topical Applications, Kelsey Marie Lopez

LSU Doctoral Dissertations

Bacteria can thrive in diverse environments and are often harmless or beneficial. Bacteria in digestive tracts is one example of beneficial bacteria; however, bacteria can be harmful and when this type proliferates, it can cause infections within hosts. Bacterial infections are easily treated with antibiotics in most cases. However, bacteria are also capable of developing mutations which could cause them to become multi-drug resistant and eventually, “superbugs.” Therefore, the development of novel antimicrobial agents and materials capable of combating drug-resistant bacteria is necessary. Research presented in this dissertation focuses on different strategies for minimizing and preventing topical bacterial infections using …

Data-Driven And Model-Based Methods With Physics-Guided Machine Learning For Damage Identification, Zhiming Zhang

LSU Doctoral Dissertations

Structural health monitoring (SHM) has been widely used for structural damage diagnosis and prognosis of a wide range of civil, mechanical, and aerospace structures. SHM methods are generally divided into two categories: (1) model-based methods; (2) data-driven methods. Compared with data-driven SHM, model-based methods provide an updated physics-based numerical model that can be used for damage prognosis when long-term data is available. However, the performance of model-based methods is susceptible to modeling error in establishing the numerical model, which is usually unavoidable due to model simplification and omission. The major challenge of data-driven SHM methods lies in data insufficiency, e.g., …

Design, Synthesis And Characterization Of New Superconductors, Xin Gui

LSU Doctoral Dissertations

Design and synthesis of new materials are a long-standing goal for chemistry, physics and material science, especially those with intriguing properties such as magnetism and superconductivity. With consideration and incorporation of the highlights in some existing design rules, we successfully designed and discovered the superconductivity in BaPt₂Bi₂, SrSnP and Yb_xPt₅P.

With the help of valence electron counting method, we synthesized a new intermetallic compound, BaIr₂Ge₂, which was then found to be non-superconducting above 1.8 K. Thus, we considered both valence electron counting and chemical pressure adjustment to reach …

Development Of Water Coning Control Design Metrics In Naturally Fractured Reservoirs, Samir Prasun

LSU Doctoral Dissertations

Naturally fractured reservoirs (NFRs) with bottom-water are known for their instant water breakthrough and severe water coning that reduces oil recovery. This is because water channels through the highly permeable fractures easily connecting the well to the aquifer bypassing the oil contained in the matrix. Remedial techniques such as producing below critical-oil rate, optimizing the well spacing and installing the downhole water sink (DWS)/ downhole water loop (DWL) technology, have already been successfully tested in single-porosity reservoirs (SPR). However, applicability of these techniques in NFRs are unknown since only a few studies have been performed on their feasibility in NFRs, …

Sediment Transport And Geomorphological Evolution In The Transgressive Ship Shoal, Louisiana: Insights From Geophysical Observation, Modeling, And Machine Learning Studies, Haoran Liu

LSU Doctoral Dissertations

Ship Shoal has been a high-priority target sand resource for dredging activities to restore the eroding barrier islands in Louisiana, USA. Many studies have been performed in Ship Shoal in recent decades, but our knowledge of temporal and spatial variations of sediment transport and post-dredge morphology is still limited. The objectives of this dissertation are to explore the sediment infilling process, the spatial and temporal evolution of the morphology of dredge pits near and on Ship Shoal by using multiple methods. Scientific methods used in this study include (a) geophysical observation using bathymetry, side-scan and subbottom technique, (b) sediment transport …

A Component Analysis Of Implementation Planning: Examining Mechanisms That Underlie A Teacher Implementation Support Strategy, James Jaran Upright

LSU Doctoral Dissertations

To maximize instructional time, teachers must be able to effectively manage student behavior. However, surveys consistently reveal that a significant portion of teachers feel underprepared to address challenging classroom behavior. One of the most effective ways to reduce problem behaviors in school is with systematic classroom management strategies, such as the good behavior game. However, teachers often struggle to effectively implement such procedures. Promising evidence has emerged for implementation planning as an effective support strategy to improve teachers’ intervention implementation. Implementation planning is a one-time consultation process for intervention procedure planning (action planning) and identification and resolution of implementation barriers …

Metabolic Network Analysis Of Filamentous Cyanobacteria, Daniel Alexis Norena-Caro

LSU Doctoral Dissertations

Cyanobacteria were the first organisms to use oxygenic photosynthesis, converting CO₂ into useful organic chemicals. However, the chemical industry has historically relied on fossil raw materials to produce organic precursors, which has contributed to global warming. Thus, cyanobacteria have emerged as sustainable stakeholders for biotechnological production. The filamentous cyanobacterium Anabaena sp. UTEX 2576 can metabolize multiple sources of Nitrogen and was studied as a platform for biotechnological production of high-value chemicals (i.e., pigments, antioxidants, vitamins and secondary metabolites). From a Chemical engineering perspective, the biomass generation in this organism was thoroughly studied by interpreting the cell as a microbial …

Multigrid Methods For Elliptic Optimal Control Problems, Sijing Liu

LSU Doctoral Dissertations

In this dissertation we study multigrid methods for linear-quadratic elliptic distributed optimal control problems.

For optimal control problems constrained by general second order elliptic partial differential equations, we design and analyze a $P_1$ finite element method based on a saddle point formulation. We construct a $W$-cycle algorithm for the discrete problem and show that it is uniformly convergent in the energy norm for convex domains. Moreover, the contraction number decays at the optimal rate of $m^{-1}$, where $m$ is the number of smoothing steps. We also prove that the convergence is robust with respect to a regularization parameter. The robust …

Empathy, Fiction, And An Educational Ecosystem: A Narrative Case Study Of A High School Ela Classroom, Danielle Marie Klein

LSU Doctoral Dissertations

This study explores how empathy exists, as an experience, in an English Language Arts classroom. The research was conducted in an 11^th grade classroom during an instructional unit with Arthur Miller’s The Crucible as the anchor text. The study relies upon Transactional Reader Response Theory (Rosenblatt, 1988) to justify the exploration of the aesthetic, evocative nature of a text. Narrative inquiry methodology was used to collect and assemble the instances of empathy as inspired by the play. Guided by Doll’s (1993) premise of the classroom as an ecological, open system with multiple contributing forces, data was collected through classroom …

A Study On The Improvement Of Data Collection In Data Centers And Its Analysis On Deep Learning-Based Applications, Dipak Kumar Singh

LSU Doctoral Dissertations

Big data are usually stored in data center networks for processing and analysis through various cloud applications. Such applications are a collection of data-intensive jobs which often involve many parallel flows and are network bound in the distributed environment. The recent networking abstraction, coflow, for data parallel programming paradigm to express the communication requirements has opened new opportunities to network scheduling for such applications. Therefore, I propose coflow based network scheduling algorithm, Coflourish, to enhance the job completion time for such data-parallel applications, in the presence of the increased background traffic to mimic the cloud environment infrastructure. It outperforms …

Copper And Ruthenium Pyridyltriazole Complexes And Their Reactivity Toward Carbon Dioxide And Water, Fatemeh Khamespanah

LSU Doctoral Dissertations

A variety of pyridyltriazole ligands are readily available via click type cycloaddition of alkynylpyridines and azides. We made functionalized tetradentate m-xylylenebis(pyridyltriazole) (m-xpt) ligands with NH₂ and NMe₂ electron-donating and NO₂ electron-withdrawing substituents on the pyridine moieties. Complexation of these ligands with Cu(II) gives dimeric macrocycles with square pyramidal geometry at Cu centers. Previous work in our lab with the unsubstituted [Cu₂(m-xpt)₂(NO₃)₂]²⁺ complex showed reduction to Cu(I) by using ascorbate as reducing agent. Oxidation of the Cu(I) solution in air results in formation of …

Investigating Geochemical Processes Of Fluid-Rock Interactions On Materials Related To Energy And Environment, Zelong Zhang

LSU Doctoral Dissertations

Understanding the potential processes of radionuclides released from nuclear waste forms is essential to the safe disposal and containment of nuclear waste. Iodoapatite, a potential waste form for radioiodine, was chosen as a model system to examine the impact by common aqueous anions on iodine release processes. Four semi-dynamic leaching tests were performed using 0.1 mol/L NaCl, Na₂CO₃, Na₃PO₄, and Na₂SO₄ solutions respectively under 90 °C, 1 bar, fixed S/V ratio 5/m (sample surface area to solution volume), and with 24-hour replacement of the leaching solutions. Solution analysis and …

Benthic Nitrogen Dynamics In Response To Deltaic Succession, Anthropogenic Fertilization And Hurricane Events In An Emerging Coastal Deltaic Floodplain Within The Mississippi River Delta Plain, Song Li

LSU Doctoral Dissertations

Increasing concentrations of nitrogenous fertilizer (NO₃^-) in rivers have potentially altered benthic nitrogen (N) cycling in coastal deltaic floodplains at the continental margins of major rivers. Here I evaluated the N removal capacity of a newly emergent coastal deltaic floodplain [Wax Lake Delta (WLD)] within the Mississippi River Delta Plain using continuous flow-through incubations. I investigated the response of benthic N dynamics in WLD to deltaic succession, anthropogenic fertilization and hurricane events. The estimated annual NO₃^- removal of 896 Mg N yr^-1 in WLD accounts for 10 to 27% of total NO₃^{- …}

Identification Of Top-Down, Bottom-Up, And Cement-Treated Reflective Cracks Using Convolutional Neural Network And Artificial Neural Network, Nirmal Dhakal

LSU Doctoral Dissertations

The objective of this study was to formulate a Convolutional Neural Networks (CNN) model and to develop a decision-making tool using Artificial Neural Networks (ANN) to identify top-down, bottom-up, and cement treated (CT) reflective cracking in in-service flexible pavements. The CNN’s architecture consisted of five convolutional layers with three max-pooling layers and three fully connected layers. Input variables for the ANN model were pavement age, asphalt concrete (AC) thickness, annual average daily traffic (AADT), type of base, crack orientation, and crack location. The ANN network architecture consisted of an input layer of six neurons, a hidden layer of ten neurons, …

Video-Based Interventions: Teaching Adults And Preschoolers, Philip Ross Richard Iii

LSU Doctoral Dissertations

Long gone are the days in which technology is looked upon as a trivial novelty. Whether evoking positive or negative reactions, advancements in technology continue to alter our daily environments. One such example is Video Based Interventions (VBI). VBI utilize video recording to facilitate the acquisition of various skills and behaviors (Rayner, Denholm, & Sigafoos, 2009). While it may sound like a simple intervention at first, many procedural variations of have been examined in research and practice. The two experiments comprising the current study examined the effectiveness of video models when used in conjunction with other instructional methods. Experiment I …

Evolution Of Computational Thinking Contextualized In A Teacher-Student Collaborative Learning Environment., John Arthur Underwood

LSU Doctoral Dissertations

The discussion of Computational Thinking as a pedagogical concept is now essential as it has found itself integrated into the core science disciplines with its inclusion in all of the Next Generation Science Standards (NGSS, 2018). The need for a practical and functional definition for teacher practitioners is a driving point for many recent research endeavors. Across the United States school systems are currently seeking new methods for expanding their students’ ability to analytically think and to employee real-world problem-solving strategies (Hopson, Simms, and Knezek, 2001). The need for STEM trained individuals crosses both the vocational certified and college degreed …

Temporal Decomposition For Multi-Interval Optimization In Power Systems, Farnaz Safdarian

LSU Doctoral Dissertations

Large optimization problems are frequently solved for power systems operation and analysis of electricity markets. Many of these problems are multi-interval optimization with intertemporal constraints. The size of optimization problems depends on the size of the system and the length of the considered scheduling horizon. Growing the length of the scheduling horizon increases the computational burden significantly and might make solving the problem in a required time span impossible. Many simplifications and approximation techniques are applied to reduce the computational complexity of multi-interval scheduling problems and make them solvable in a reasonable time span. Geographical decomposition is presented in the …

Synthesis, Characterization, And Investigation Of Metal Ion Quenching In Fluorescent Carbon Dot Surrogates For Particulate Matter Black Carbon And Evaluation Of Cellular Health Effects Due To The Surrogate Materials, Christopher Lee Sumner Jr

LSU Doctoral Dissertations

Black carbon (BC) is an environmental pollutant of particular concern to many international organizations for both its health effects and environmental effects. Probing health effects of BC as produced in the environment is difficult due to the complex nature of environmental pollutants found in their naturally occurring state. Fluorescent carbon dots (FCDs) were chosen to be used as a surrogate for BC. In the process of examining FCDs and their behavior as surrogates, information was gained on the health effects and behavior of FCDs as a class of nanomaterials for cell and tissue studies, which is outlined in this dissertation. …

Predictive Modeling Of Asynchronous Event Sequence Data, Jin Shang

LSU Doctoral Dissertations

Large volumes of temporal event data, such as online check-ins and electronic records of hospital admissions, are becoming increasingly available in a wide variety of applications including healthcare analytics, smart cities, and social network analysis. Those temporal events are often asynchronous, interdependent, and exhibiting self-exciting properties. For example, in the patient's diagnosis events, the elevated risk exists for a patient that has been recently at risk. Machine learning that leverages event sequence data can improve the prediction accuracy of future events and provide valuable services. For example, in e-commerce and network traffic diagnosis, the analysis of user activities can be …

Combinatorial And Asymptotic Statistical Properties Of Partitions And Unimodal Sequences, Walter Mcfarland Bridges

LSU Doctoral Dissertations

Our main results are asymptotic zero-one laws satisfied by the diagrams of unimodal sequences of positive integers. These diagrams consist of columns of squares in the plane; the upper boundary is called the shape. For various types of unimodal sequences, we show that, as the number of squares tends to infinity, 100% of shapes are near a certain curve---that is, there is a single limit shape. Similar phenomena have been well-studied for integer partitions, but several technical difficulties arise in the extension of such asymptotic statistical laws to unimodal sequences. We develop a widely applicable method for obtaining these limit …

New Synthetic Transformations Utilizing Silyloxyallyl Cations And Epoxonium Ions As Reactive Intermediates, Alexander Houston Cleveland

LSU Doctoral Dissertations

The development of new chemical transformations is of paramount importance in organic chemistry. In fact the study and creation of new reactions often uncovers new chemical reactivities and creates a new area of chemistry. The purpose of this dissertation is to present the development of new synthetic reactions that were uncovered through previous discoveries. Additionally the underlying theme of this work relies on the intermediacy of cationic reactive intermediates such as silyloxyallyl cations and epoxonium ions. Chapters 1 and 2 present the reactivity of novel silyloxyallyl cations. These cationic species are generated via the mild ionization of a-hydroxy silylenol ethers …

Behavior Of Iron Species And Free Radicals In Ambient Pm2.5 And Pm Surrogates, Cholena Russo Ren

LSU Doctoral Dissertations

Air pollution, consisting of ambient particulate matter (PM), has been a rising health concern to the public. PM contains free radicals and have been known to damage human cells; however, their free radical chemistry is not well understood. This study utilized various vacuum and/or heat treatments to study free radical behavior in PM_2.5 (particulate matter with an aerodynamic diameter of 2.5 mm or less) and PM surrogates and simulated sunlight effects on PM_2.5. To mimic PM, iron-silica catalysts (i.e. PM surrogates) were synthesized and real-world ambient PM_2.5 was selected. The free radicals in PM_{2.5 …}

Information Retrieval-Based Optimization Approaches For Requirement Traceability Recovery, Danissa Victoria Rodriguez Caraballo

LSU Doctoral Dissertations

Requirements traceability provides support for important software engineering activities. Requirements traceability recovery (RTR) is becoming increasingly important due to the numerous benefits to the overall quality of software. Improving the RTR problem has become an active topic of research for software engineers; researchers have proposed a number of approaches for improving and automating RTR across the requirements and the source code of the system. Textual analysis and Information Retrieval (IR) techniques have been applied to the RTR problem for many years; however, most of the existing IR-based methodologies applied to the RTR problem are semiautomatic or time-consuming, even though many …

Accurate Tracking Of Position And Dose During Vmat Based On Vmat-Ct, Xiaodong Zhao

LSU Doctoral Dissertations

Purpose: Local tomography reconstruction is achievable with EPID images acquired during VMAT and was named as VMAT-CT. However, it did not gain popularity due to multiple limitations and technical challenges. The goal of this study was to extend VMAT-CT concept, generate complete 3D or 4D CT images and dose, track and adapt VMAT plan based on updated images and dose.

Methods: We considered collimator angle and removed blurred areas in EPID images for VMAT-CT reconstruction to reduce artifacts and improve image quality. VMAT-CT+ images were generated by fusing VMAT-CT and planning CT using rigid or deformable registration. For 4D SBRT …