Digital Commons Network^™

Monitoring Molecular Interactions With Cell Membranes Using Time-Dependent Second Harmonic Generation Microscopy, Prakash Hamal, Sushant P. Sahu, Peter P. Piers, Huy Nguyen, Shashank S. Kamble, Robin L. Mccarley, Manas R. Gartia, Louis H. Haber

Faculty Publications

Time-resolved second harmonic generation (SHG) microscopy is used to investigate the physicochemical interactions between positively charged, hydrophobic, drug-like molecules and the plasma membrane of human cells (nonsmall cell lung cancer, H596). In the present study, molecular adsorption and transport of the cationic molecules, malachite green (MG) and malachite green isothiocyanate (MGITC), are studied in real time in living H596 cells and in dead, fixed H596 cells. MGITC is shown to have stronger adsorption and more rapid transport kinetics as compared to MG due to increased dipole-dipole interactions. Additionally, MGITC is found to have faster adsorption and transport kinetics in living …

The Passive-Active Interaction (Pai) Model: Redefining Audio Interactions In Video Game Music, Morgan A. Weeks

LSU Doctoral Dissertations

Scholarship on music in video games has focused on the player in two main ways: the psychological effect music has on the player and the physical, kinesthetic relationship between the player’s inputs and the game’s music. This dissertation builds on this work by exploring gameplay moments in which the music informs the player’s inputs through rhythms, tempo, harmonic relationships, and changes in the musical texture. Using “analytical play” (Summers 2016), rhythmic analysis, looping analysis, and harmonic observations, alongside a variety of different video games, consoles and genres, I have developed an analytical Passive-Active Interaction (PAI) Model that is applicable to …

The Recusant's Dream, Isabella Temperville

LSU Master's Theses

The Recusant’s Dream is a collection of works that portray the overarching lore of an original narrative by Isabella Temperville. Inspired by Biblical narratives, The Recusant’s Dream tells the story of Lucifer’s rebellion against an order of power-hungry archangels and the consequences that follow in the form of an all-consuming curse. The curse is both a marker and a death sentence, as those who bear it are called “demons” and are fated to eventually succumb to it. Lucifer was the first to fall victim to the consumption and his death sparked an infernal war amongst the cursed and the order …

How Financial Aid Affects The Odds Of Study Abroad Participation For Students Of Color, Patrick Newcomb

LSU Doctoral Dissertations

Prior research has shown that studying abroad provides students with enriching, diverse educational experiences with positive personal, academic, and professional outcomes. Despite the benefits, only a small portion of American higher education students participate in study abroad programs. Students of color disproportionately study abroad at lower rates than White students. Since cost is often cited as the primary barrier preventing education abroad, this study examined the types of financial aid associated with study abroad access and participation.

This study used data from the National Postsecondary Student Aid Study, which is a nationwide dataset designed to represent the makeup of institutions …

The Influence Of Selected Demographic And Academic Factors On The Persistence To Degree Completion Of Military Veterans At A Research University In The South, Damon L. Ploger

LSU Doctoral Dissertations

A large number of veterans leave the military each year, hoping to reacclimate successfully to civilian society while utilizing the knowledge and skills they acquired in the military to assist in their pursuit of gainful employment. Many wish to enhance this process by earning a college degree. Unfortunately, various barriers and other random personal hurdles can impede the progress of the now-veteran student toward degree completion. The lack of knowledge about these barriers and the factors that support a veteran student’s persistence to complete a college degree has created the need for this investigation. The primary purpose of this study …

Geo-Ai For Wetland Classification And Evolutionary Analysis, Lirong Yin

LSU Doctoral Dissertations

Wetlands, as a crucial component of the Earth's ecosystem, play a vital role in maintaining ecological balance and preserving biodiversity. However, wetlands are currently facing severe challenges, as both natural and human-induced factors are contributing to their global degradation. Gaining a deep understanding of the species composition and biodiversity within wetland-covered areas and accurately analyzing their changing trends not only helps assess the current and future state of wetlands but also provides strong support for the formulation of scientifically sound wetland conservation strategies. In recent years, the rapid development of geospatial intelligence and remote sensing technologies has brought new opportunities …

Understanding The Experiences Of Biology Teachers During The Covid-19 Pandemic, Amber R. Collins

LSU Doctoral Dissertations

ABSTRACT

The 2020 COVID-19 Pandemic has caused the world to focus on the transition of learning environments that are more digital and virtual than any other time in educational history. Schools all over the world were required to adjust not only the mode of instruction, such as in virtual, hybrid, or in-person, but also create guidelines and procedures that reduce the amount of interaction between the teacher and the student (Garbe, Ogurlu, Uzeyir, & Cook, 2020). The research questions that guided this study were: 1) What are the experiences of five Biology teachers during the COVID-19 pandemic in transitioning to …

Quantitative Risk Analysis For Elections, George A. Buras

LSU Master's Theses

This paper examines risk analysis and risk management in the field of election security. The purpose of this paper is not to enumerate risks to election security or explain how they might be mitigated, but rather to understand and improve how we measure and communicate those risks.

First, I contextualize election security risks by establishing what it means for an election to be secure and I give an overview of the types of events that might threaten election security. Then, I explore different methods that we can use to model electoral risks. Existing resources for managing electoral risks use qualitative …

Assessing Groundwater Availability And Land Subsidence Risk Associated With Anthropogenic Activities In A Complex Aquifer System, Aya Bakr Attya Mohamed

LSU Doctoral Dissertations

The Southern Hills aquifer system (SHAS) is the primary source of water in the Capital area of Louisiana. However, the overexploitation of freshwater-bearing aquifers and the presence of two active faults, the BR fault and the DSS fault, have resulted in groundwater depletion, saltwater intrusion, and increased the risk of land surface subsidence. Such critical issues pose substantial threats to groundwater availability and exert detrimental effects on the environment and urban infrastructures. This dissertation presents a comprehensive investigation of the SHAS for recognizing the consequences of groundwater depletion and its potential long-term impacts on groundwater availability and land stability. A …

Rheological, Interfacial, And Filtration Behavior Of Lignocellulosic Nanomaterials In Suspension And Emulsion Drilling Fluids, Meen Sung Koo

LSU Doctoral Dissertations

In recent years, the rheological aspects of suspensions/emulsions applied by cellulose nanomaterials (CNMs) have been gained considerable interests due to high gel-forming properties ascribed by hydrophilicity, crystallinity, ease functionalization, and high aspect ratio. Introducing residual lignin in CNMs (LCNMs) seemed to be capable of achieving various advantages in the application of CNMs ascribed by hydrophobicity, binding effects, and abundant aromatic groups derived from complexity of lignin. This dissertation dedicates to the characterizations of (L)CNMs, and rheological properties of (L)CNMs applied fluids (i.e., suspension and emulsion). In the suspension system, the presence of lignin in LCNMs decreased gel strength, viscosity, and …

Quaternary Subsurface Characterization Of The Mississippi River Valley Alluvial Aquifer: Insights From Interval Kriging And Airborne Em-Borehole Data Integration, Yuqi Song

LSU Doctoral Dissertations

The Pleistocene period significantly contributed to the formation of alluvial aquifer worldwide. These productive aquifers are crucial for domestic, industrial, and agricultural water supplies. The Mississippi River Valley alluvial aquifer (MRVA), a principal aquifer in the U.S., is crucial for national food security and global agricultural supply. This study aims to characterize the subsurface architecture of the MRVA, thereby enhancing fundamental understanding of sedimentological processes involved in the genesis of glacio-fluvial aquifers worldwide. The research objectives are threefold: (1) to provide a detailed characterization of the MRVA; (2) to develop 3D geostatistical methods for geological modeling; and (3) to develop …

Abundance And Prevalence Of Antibiotic-Resistant Escherichia Coli In Tangipahoa Parish, Louisiana Water Bodies Impacted By On-Site Wastewater Treatment System Effluent, Katherine Weise

LSU Master's Theses

Antimicrobial resistance (AMR) is a growing public health concern, especially with the spread of extended-spectrum beta-lactamase (ESBL) producing Escherichia coli. This study examined the prevalence and abundance of antibiotic-resistant E. coli in Yellow Water (YW) and Natalbany River (NR) in Tangipahoa Parish, Louisiana, which receive effluent from decentralized wastewater treatment systems. Monthly surface water grab samples were collected at four sites on each river from February 2023 to July 2024 and screened for generic and antibiotic-resistant E. coli using membrane filtration with ceftriaxone and cefotaxime as screening agents per the WHO Tricycle Protocol. We evaluated resistance patterns of the …

Stochastic Analysis And White Noise Calculus Of Nonlinear Wave Equations With Application To Laser Generation And Propagation, Sivaguru S. Sritharan, Saba Mudaliar

Journal of Stochastic Analysis

No abstract provided.

Deep Learning Applications For Predictive Modeling In Cancer Therapy And Enzyme Encoding, Mengmeng Liu

LSU Doctoral Dissertations

Predictive modeling has revolutionized computational biology and molecular bioinformatics, enabling significant advancements in cancer therapy and functional enzyme characterization. Despite considerable progress, significant challenges remain in accurately predicting combinational cancer therapies and systematically representing enzyme functions for computational applications. Traditional methods struggle with capturing the complex interactions between drugs and biological networks, as well as representing hierarchical relationships within enzyme classifications. This dissertation addresses these limitations by developing advanced deep learning models tailored to enhance predictive performance in both domains.

First, a data augmentation strategy is introduced to improve anticancer drug synergy prediction by generating pharmacologically relevant drug pairs based …

Improving The Stability And Selectivity Of Methane Dry Reforming Catalysis Through Active Site And Process Tuning, Jonathan Lucas

LSU Doctoral Dissertations

Dry reforming of methane (DRM) is a potential industrial solution to greenhouse emissions whereby CH₄ and CO₂ are reacted on a transition metal catalyst to produce syngas, a feed stock for higher value chemical products. Ni can be used as the catalyst for DRM replacing the high cost and low abundance noble metals (Pt, Pd, Rh). However, the harsh process conditions of DRM (T > 700°C, P of 1-10 bar) readily deactivate Ni through coking and sintering. Ni supported on reducible oxides, specifically CeO₂ and CeO₂-ZrO₂ (CZO), have been widely studied to combat the rapid …

Bayesian Network-Based Framework To Uncover Social Inequities In Flood Risk: Application To East Baton Rouge Parish, Louisiana, Fuad Hasan

LSU Master's Theses

Regional flood risk assessment requires understanding the complex interplay of sociodemographic, socioeconomic, hydrogeologic, built environment, and climatic variables that impact flood vulnerability. Traditional studies often focus on large-scale units, overlooking localized variations and disproportionate exposure within populations. To address these gaps, a methodological framework of flood risk assessment using the Bayesian network was proposed and applied to East Baton Rouge Parish, Louisiana, for the August 2016 flood event to identify relationships between flood risk variables at the housing unit level. Flood exposure representativeness (FER) was determined using the Bayesian network's inference capabilities to identify over- or under-represented groups. This study …

Investigating Spatial Mapping Of Lipid And Protein Alterations Within Cells And Tissues Using Raman Microspectroscopy, Elnaz Sheikh

LSU Doctoral Dissertations

The progression of various diseases is associated with alterations in the microenvironment of cells, consisting of a variety of metabolites like lipids and proteins. It is well known that lipids and proteins are potential biomarkers for indicating alterations within the cell microenvironment induced by disease, and various methods are frequently used for their examination. To understand the chemical composition and spatial distribution of constituents in tissues and cells, confocal Raman spectroscopy and microscopy, as non-destructive tools, have shown potential for monitoring abnormalities at the cellular level with high resolution and can facilitate detection through targeting multiple biomarkers. The application of …

Layer-Dependent Spin-Resolved Electronic Structure Of Ferromagnetic Triple-Layered Ruthenate Sr4ru3 O10, Prosper Ngabonziza, Jonathan D. Denlinger, Alexei V. Fedorov, Gang Cao, J. W. Allen, G. Gebreyesus, Richard M. Martin

Faculty Publications

High-resolution angle- and spin-resolved photoemission spectroscopy (ARPES) of the triple-layered ruthenate Sr4Ru3O10 reveals features of the electronic structure that extend our understanding of the layered strontium ruthenates. The spectra near the Fermi energy are very different from the nonmagnetic analogues Sr2RuO4 and Sr3Ru2O7 with distinct Fermi surfaces for wide electronlike minority spin bands around the zone center and narrow holelike majority spin Fermi surface contours around the zone corners. The most dramatic results are two narrow spectral peaks ∼30 meV below the Fermi level, a spin-minority holelike band at the Brillouin zone center, and a spin-majority saddle-band van Hove singularity …

Ec2vec: A Machine Learning Method To Embed Enzyme Commission (Ec) Numbers Into Vector Representations, Mengmeng Liu, Xialong Ni, J. Ramanujam, Michal Brylinski

Faculty Publications

Enzyme commission (EC) numbers play a vital role in classifying enzymes and understanding their functions in enzyme-related research. Although accurate and informative encoding of EC numbers is essential for enhancing the effectiveness of machine learning applications, simple EC encoding approaches suffer from limitations such as false numerical order and high sparsity. To address these issues, we developed EC2Vec, a multimodal autoencoder that preserves the categorical nature of EC numbers and leverages their hierarchical relationships, resulting in more meaningful and informative representations. EC2Vec encodes each digit of the EC number as a categorical token and then processes these embeddings through a …

Trans-Arg: Predicting Antibiotic Resistance Genes With A Transformer-Based Model And Pretrained Protein Language Model, Mohd Manzar Abbas, Amit Ranjan, Aixin Hou, Supratik Mukhopadhyay

Faculty Publications

Antibiotic resistance presents an emerging challenge to global health by reducing the efficacy of antibiotics administered to treat bacterial infections. Traditional approaches for detecting antibiotic resistance genes (ARGs) involve alignment-based sequence similarity techniques, which are time-consuming and resource-intensive. This signifies the necessity for developing advanced computational methods to detect ARGs early. To address this challenge, we introduce Trans-ARG, a novel multi-head attention transformer-based model designed to predict potential ARGs. Our approach leverages the pretrained ESMFold model to extract embeddings from protein sequences, capturing intricate structural and functional information. Protein sequences labelled as ARG or non-ARG were used as the dataset. …

Kg-Dta: A Knowledge Graph-Based Meta-Path Learning Framework To Predict Drug-Target Binding Affinity, Amit Ranjan, Adam Bess, Md Saiful Islam Sajol, Magesh Rajasekaran, Chris Alvin, Supratik Mukhopadhyay

Faculty Publications

Drug target affinity (DTA) prediction is essential at different phases of drug discovery and virtual drug screening. However, traditional wet lab experiments are time and resource-intensive owing to the complex interactions within the vast biological and chemical spaces. Computational methods have proven their potential to predict DTA, but none have considered the association of drugs and proteins to capture the complex interactions in the biological network between drugs and proteins. To address this, we propose a novel framework leveraging knowledge graph-based meta-path learning (KG-DTA) to enhance DTA prediction. First, we construct a weighted heterogeneous network of drugs and proteins that …

High-Resolution Model Intercomparison Project Phase 2 (Highresmip2) Towards Cmip7, Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis Philippe Caron, Ping Chang, Cheng Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh Ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki

Faculty Publications

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) …

Modelling The Effects Of Vegetation Distribution And Density On Hydrological Connectivity And Water Age In A River Delta, Madoche Jean Louis, Matthew Hiatt

Faculty Publications

Water transport timescales (WTTs) quantify how long it takes for water to travel through or remain in a system and are often cast as indicators of ecosystem function and health. Such timescales are known to be affected by vegetation in various environments. We quantify the impact of floodplain vegetation on WTTs within the Wax Lake Delta (WLD), a river delta system in Louisiana, USA, using a high-resolution Delft3D Flexible Mesh (DFM) model incorporating vegetation-induced flow resistance. We show that increased vegetation density leads to extended WTTs within vegetated sections of WLD while fostering flow localization and accelerating transport within distributary …

Multiwavelength Analysis Of At 2023sva: A Luminous Orphan Afterglow With Evidence For A Structured Jet, Gokul P. Srinivasaragavan, Daniel A. Perley, Anna Y.Q. Ho, Brendan O’Connor, Antonio De Ugarte Postigo, Nikhil Sarin, S. Bradley Cenko, Jesper Sollerman, Lauren Rhodes, David A. Green, Dmitry S. Svinkin, Varun Bhalerao, Gaurav Waratkar, A. J. Nayana, Poonam Chandra, M. Coleman Miller, Daniele B. Malesani, Geoffrey Ryan, Suryansh Srijan, Eric C. Bellm, Eric Burns, David J. Titterington, Maria B. Stone, Josiah Purdum, Tomás Ahumada, G. C. Anupama, Sudhanshu Barway, Michael W. Coughlin, Andrew Drake, Rob Fender, José F. Agüí Fernández, Dmitry D. Frederiks, Stefan Geier

Faculty Publications

We present multiwavelength analysis of ZTF23abelseb (AT 2023sva), an optically discovered fast-fading (∆mr = 2.2 mag in ∆t = 0.74 d), luminous (Mr ∼ −30.0 mag), and red (g − r = 0.50 mag) transient at z = 2.28 with accompanying luminous radio emission. AT 2023sva does not possess a γ -ray burst (GRB) counterpart to an isotropic equivalent energy limit of Eγ,iso < 1.6 × 10⁵² erg, determined through searching γ -ray satellite archives between the last non-detection and first detection, making it the sixth example of an optically discovered afterglow with a redshift measurement and no detected GRB counterpart. We analyse …

Ixpe Observation Of The Low-Synchrotron Peaked Blazar S4 0954+65 During An Optical-X-Ray Flare, Pouya M. Kouch, Ioannis Liodakis, Francesco Fenu, Haocheng Zhang, Stella Boula, Riccardo Middei, Laura Di Gesu, Georgios F. Paraschos, Iván Agudo, Svetlana G. Jorstad, Elina Lindfors, Alan P. Marscher, Henric Krawczynski, Michela Negro, Kun Hu, Dawoon E. Kim, Elisabetta Cavazzuti, Manel Errando, Dmitry Blinov, Anastasia Gourni, Sebastian Kiehlmann, Angelos Kourtidis, Nikos Mandarakas, Nikolaos Triantafyllou, Anna Vervelaki, George A. Borman, Evgenia N. Kopatskaya, Elena G. Larionova, Daria A. Morozova, Sergey S. Savchenko, Andrey A. Vasilyev, Ivan S. Troitskiy, Tatiana S. Grishina

Faculty Publications

The X-ray polarization observations, made possible with the Imaging X-ray Polarimetry Explorer (IXPE), offer new ways of probing high-energy emission processes in astrophysical jets from blazars. Here, we report the first X-ray polarization observation of the blazar S4 0954+65 in a high optical and X-ray state. During our multi-wavelength (MWL) campaign of the source, we detected an optical flare whose peak coincided with the peak of an X-ray flare. This optical-X-ray flare most likely took place in a feature moving along the parsec-scale jet, imaged at 43 GHz by the Very Long Baseline Array (VLBA). The 43 GHz polarization angle …

Structural And Magnetic Properties Of Cotemo O6, Yu Li, Jared Coles, Xin Gui, Hyowon Park, Yan Wu, Xinglong Chen, Jing Han Chen, Xiaoping Wang, Huibo Cao, Shane Stadler, Omar Chmaissem, David P. Young, Stephan Rosenkranz, John F. Ditusa

Faculty Publications

We have conducted a comprehensive investigation into the magnetic properties of the chiral multiferroic material CoTeMoO6. In contrast with the previous claim of canted antiferromagnetic order with ferromagnetic components [Y. Doi, J. Solid State Chem. 182, 3232 (2009)10.1016/j.jssc.2009.09.008], our investigation reveals an antiferromagnetic ground state with compensated moments, providing an interesting platform for exploring exotic material properties. Through careful measurements of magnetization under a series of applied fields, we demonstrate that there exist two sequential field-induced magnetic transitions in CoTeMoO6, with one occurring at Hc1=460 Oe along the a axis, and the other at Hc2=1.16 T with the field along …

Post-Wildfire Mobilization Of Organic Carbon, Travis Numan, Srinidhi Lokesh, Abrar Shahriar, Anil Timilsina, Myron L. Lard, Justin Clark, Yasaman Raeofy, Qian Zhao, Simon R. Poulson, Paul S. Verburg, Jocelyn A. Richardson, Robert L. Cook, Vera Samburova, Yu Yang

Faculty Publications

Wildfires significantly alter watershed functions, particularly the mobilization of organic carbon (OC). This study investigated OC mobility and the physicochemical characteristics of wildfire-impacted soils and ashes from the northern California and Nevada fires (Dixie, Beckworth, Caldor). Organic carbon in wildfire-derived ashes (9.2–57.3 mg/g) generally exceeded levels in the background soils (4.3–24.4 mg/g), except at the Dixie fire sites. The mobile OC fraction varied from 0.0093 to 0.029 in ashes and 0.010 to 0.065 in soils, though no consistent trend was observed between the ashes and soils. Notably, the ash samples displayed lower OC mobility compared with the soils beneath them. …

The Contemporary Distribution Of Scincine Lizards Does Not Reflect Their Biogeographic Origin, Aniruddha Datta-Roy, Matthew C. Brandley, Christopher C. Austin, Aaron M. Bauer, David James Harris, Salvador Carranza, Kanishka D.B. Ukuwela, Anslem De Silva, Krystal A. Tolley, K. Praveen Karanth, Maitreya Sil

Faculty Publications

Aim: We assess the systematic relationships and historical biogeographic patterns in the subfamily Scincinae, a group of lizards that primarily inhabits the Afro-Madagascan and Saharo-Arabian regions with isolated lineages in Europe, North America, East Asia, India and Sri Lanka. The contemporary distribution of these lineages on the historical Laurasian and Gondwanan landmasses make scincines an ideal system to study the roles of vicariance and dispersal on a geologic scale of tens of millions of years. Location: Global. Taxon: Subfamily Scincinae (Family Scincidae). Methods: We conducted biogeographic analyses on a reconstructed, time-calibrated species tree of scincine genera, including members of the …

Comparing The Restoration Effect And Stress Recovery In Real And Virtual Environments With A Green Wall, Alireza Sedghikhanshir, Yan Chen, Yimin Zhu, Melissa R. Beck, Amirhosein Jafari

Faculty Publications

Biophilic design, incorporating natural elements, is known to enhance stress recovery. Immersive virtual environments (IVEs) are increasingly utilized for biophilic design validation and research, but their efficacy in replicating the restorative effects of real environments remains uncertain. Varying responses to virtual settings suggest that specific design factors may affect their effectiveness. This study provides a novel comparison of the stress recovery and restoration effect between real and virtual green walls in a controlled climate chamber. Sixty-three participants were exposed to either a real or virtual green wall for seven minutes after a 5 min stressor task. Physiological stress responses, including …

Time-Series Data-Driven Pm2.5 Forecasting: From Theoretical Framework To Empirical Analysis, Chunlai Wu, Ruiyang Wang, Siyu Lu, Jiawei Tian, Lirong Yin, Lei Wang, Wenfeng Zheng

Faculty Publications

PM2.5 in air pollution poses a significant threat to public health and the ecological environment. There is an urgent need to develop accurate PM2.5 prediction models to support decision-making and reduce risks. This review comprehensively explores the progress of PM2.5 concentration prediction, covering bibliometric trends, time series data characteristics, deep learning applications, and future development directions. This article obtained data on 2327 journal articles published from 2014 to 2024 from the WOS database. Bibliometric analysis shows that research output is growing rapidly, with China and the United States playing a leading role, and recent research is increasingly focusing on data-driven …