Digital Commons Network^™

Aircraft Wastewater Surveillance For Early Detection Of Sars-Cov-2 Variants — John F. Kennedy International Airport, New York City, August–September 2022, Robert C. Morfino, Stephen M. Bart, Andrew Franklin, Benjamin H. Rome, Andrew P. Rothstein, Thomas W.S. Aichele, Siyao Lisa Li, Aaron Bivins, Ezra T. Ernst, Cindy R. Friedman

Faculty Publications

No abstract provided.

Machine Learning Approach For Predicting Bridge Components’ Condition Ratings, Md Manik Mia, Sabarethinam Kameshwar

Faculty Publications

Information on bridge condition rating is critical to make decisions regarding rehabilitation or replacement of bridges. Currently, bridge components’ condition ratings are evaluated manually using inspection reports. Markov chain and Petri net models are most commonly used for predicting future values of bridge parameters, however, applicability of these models for a regional or statewide portfolio of bridges may be limited. The existing data based models have low prediction accuracy. Hence, a data and machine learning based approach is presented herein for predicting the future condition values of major components—deck, superstructure and substructure—in a portfolio of bridges with an objective to …

Semi-Parametric Control Architecture For Autonomous Underwater Vehicles Subject To Time Delays, Ignacio Carlucho, Dylan Stephens, William Ard, Corina Barbalata

Faculty Publications

This paper presents a data-driven model-based control system for autonomous underwater vehicles (or AUVs) subject to input delays. This work is motivated by the input time delays that can arise in underwater robotics due to communication restrictions and sensor malfunctions. Such delays can highly degrade the performance of classical control structures resulting in unpredictable system behaviours. The proposed control architecture addresses such limitations. The approach incorporates a linear dynamic representation of the system obtained using the Koopman operator in an observer/state prediction formulation. The proposed control architecture is designed based on discrepancies between the data-driven estimation of the system's behaviour …

Event-Triggered Control Under Unknown Input And Unknown Measurement Delays Using Interval Observers, Michael Malisoff, Frederic Mazenc, Corina Barbalata

Faculty Publications

We provide a new input-to-state stabilizing event-triggered feedback design for linear systems with unknown input delays, unknown measurement delays, and unknown additive disturbances. Our trigger times are computed using only the matrices defining the system and time-lagged sampled state values. We use the theory of positive systems, interval observers, and a vector version of Halanay's inequality. We illustrate our method using a marine robotic model.

Ransomware Detection Using Federated Learning With Imbalanced Datasets, A. Vehabovic, H. Zanddizari, N. Ghani, G. Javidi, S. Uluagac, M. Rahouti, E. Bou-Harb, M. Safaei Pour

Faculty Publications

Ransomware is a type of malware which encrypts user data and extorts payments in return for the decryption keys. This cyberthreat is one of the most serious challenges facing organizations today and has already caused immense financial damage. As a result, many researchers have been developing techniques to counter ransomware. Recently, the federated learning (FL) approach has also been applied for ransomware analysis, allowing corporations to achieve scalable, effective detection and attribution without having to share their private data. However, in reality there is much variation in the quantity and composition of ransomware data collected across multiple FL client sites/regions. …

Simulating Stellar Merger Using Hpx/Kokkos On A64fx On Supercomputer Fugaku, Patrick Diehl, Gregor Dais, Kevin Huck, Dominic Marcello, Sagiv Shiber, Hartmut Kaiser, Dirk Pfluger

Faculty Publications

The increasing availability of machines relying on non-GPU architectures, such as ARM A64FX in high-performance computing, provides a set of interesting challenges to application developers. In addition to requiring code portability across different parallelization schemes, programs targeting these architectures have to be highly adaptable in terms of compute kernel sizes to accommodate different execution characteristics for various heterogeneous workloads. In this paper, we demonstrate an approach to code and performance portability that is based entirely on established standards in the industry. In addition to applying Kokkos as an abstraction over the execution of compute kernels on different heterogeneous execution environments, …

Improving Social Media Use For Disaster Resilience: Challenges And Strategies, Nina S.N. Lam, Michelle Meyer, Margaret Reams, Seungwon Yang, Kisung Lee, Lei Zou, Volodymyr Mihunov, Kejin Wang, Ryan Kirby, Heng Cai

Faculty Publications

This paper develops a social media-disaster resilience analysis framework by categorizing types of social media use and their challenges to better understand and assess its role in disaster resilience research and management. The framework is derived primarily from several case studies of Twitter use in three hurricane events in the United States–Hurricanes Isaac, Sandy, and Harvey. The paper first outlines four major contributions of social media data for disaster resilience research and management, which include serving as an effective communication platform, providing ground truth information for emergency response and rescue operations, providing information on people’s sentiments, and allowing predictive modeling. …

Achieving Online And Scalable Information Integrity By Harnessing Social Spam Correlations, Hailu Xu, Pinchao Liu, Boyuan Guan, Qingyang Wang, Dilma Da Silva, Liting Hu

Faculty Publications

Malicious web links, social rumors, fraudulent advertisements, faked comments, and biased propaganda are overwhelmingly influencing online social networks. Enabling information integrity is a hot topic in both academia and industry. Traditional social spam detection techniques rely on centralized processing, focusing only on one specific set of data sources, thereby ignoring the social spam correlations between distributed data sources. In this paper, we propose an online and scalable misinformation detection system, named Spiral, to uncover social spam by leveraging the correlations between different social data sources in geo-distributed sites. The key insight in our approach is to amplify the effectiveness of …

Historical Global And Regional Spatiotemporal Patterns In Daily Temperature, Md Adilur Rahim, Robert V. Rohli, Rubayet Bin Mostafiz, Nazla Bushra, Carol J. Friedland

Faculty Publications

The abrupt increase in surface air temperature over the last few decades has received abundant scholarly and popular attention. However, less attention has focused on the specific nature of the warming spatially and seasonally, using high-resolution reanalysis output based on historical temperature observations. This research uses the European Centre for Medium-range Weather Forecasts (ECMWF) Reanalysis Version 5 (ERA5) output to identify spatiotemporal features of daily mean surface air temperature, defined both as the mean of the maximum and minimum temperatures over the calendar day (“meanmaxmin”) and as the mean of the 24 hourly observations per day (“meanhourly”), across the terrestrial …

Analytical Advances In Homeowner Flood Risk Quantification Considering Insurance, Building Replacement Value, And Freeboard, Md Adilur Rahim, Rubayet Bin Mostafiz, Carol J. Friedland, Robert V. Rohli, Nazla Bushra

Faculty Publications

An accurate economic loss assessment for natural hazards is vital for planning, mitigation, and actuarial purposes. The widespread and costly nature of flood hazards, with the economically disadvantaged disproportionately victimized population, makes flood risk assessment particularly important. Here, flood risk is assessed as incurred by the homeowner vs. the flood insurer for insured U.S. properties through the derivation of average annual loss (AAL). AAL is estimated and partitioned using Monte Carlo simulation at the individual home scale, considering insurance coverage and deductible, and the first-floor height (i.e., height of the first floor above the ground), to determine the AAL proportion …

Freeboard Life-Cycle Benefit-Cost Analysis Of A Rental Single-Family Residence For Landlord, Tenant, And Insurer, Ehab Gnan, Rubayet Bin Mostafiz, Md Adilur Rahim, Carol J. Friedland, Robert V. Rohli, Arash Taghinezhad, Ayat Al Assi

Faculty Publications

Flood risk to single-family rental housing remains poorly understood, leaving a large and increasing population underinformed to protect themselves, including regarding insurance. This research introduces a life-cycle benefit-cost analysis for the landlord, tenant, and insurer [i.e., (U.S.) National Flood Insurance Program (NFIP)] to optimize freeboard [i.e., additional first-floor height above the base flood elevation (BFE)] selection for a rental single-family home. Flood insurance premium; apportioned flood risk among the landlord, tenant, and NFIP by insurance coverage and deductible; rental loss; moving and displacement costs; freeboard construction cost; and rent increase upon freeboard implementation are considered in estimating net benefit (NB) …

Flood Damage And Shutdown Times For Industrial Process Facilities: A Vulnerability Assessment Process Framework, Carol J. Friedland, Fatemeh Orooji, Ayat Al Assi, Matthew L. Flynn, Rubayet Bin Mostafiz

Faculty Publications

Much of the U.S. petrochemical infrastructure is heavily concentrated along the western coast of the Gulf of Mexico within the impact zone of major tropical cyclone events. Flood impacts of recent tropical disturbances have been exacerbated by an overall lack of recognition of the vulnerabilities to process systems from water intrusion, as well as insufficient disaster mitigation planning. Vulnerability assessment methods currently call for the aggregation of qualitative data to survey the susceptibility of industrial systems to floodwater damage. A means to quantify these consequences is less often employed, resulting in a poor translation of the threat of flood hazards …

Material Quantities And Estimated Construction Costs For New Elevated Irc 2015-Compliant Single-Family Home Foundations, Yamini Kodavatiganti, Md Adilur Rahim, Carol J. Friedland, Rubayet Bin Mostafiz, Arash Taghinezhad, Shandy Heil

Faculty Publications

Residential foundation selection is critical for the lifetime performance of the project, but the type of foundation selected can depend on cost. This study aims to compare the new construction costs of residential slab-on-fill and four types of crawl space foundations for residential projects by quantifying the material quantities for each and exploring the effect of building characteristics on material quantities and total costs. The building characteristics selected are size (139 m2, 186 m2, and 232 m2), footprint aspect ratio (1:1, 1:2.5, and 1:5) and first floor elevation (0 m–1.2 m in 0.3 m increments). We find that material quantities …

Homeowner Flood Risk And Risk Reduction From Home Elevation Between The Limits Of The 100- And 500-Year Floodplains, Ayat Al Assi, Rubayet Bin Mostafiz, Carol J. Friedland, Robert V. Rohli, Md Adilur Rahim

Faculty Publications

Floods inflict significant damage even outside the 100-year floodplain. Thus, restricting flood risk analysis to the 100-year floodplain (Special Flood Hazard Area (SFHA) in the United States of America) is misleading. Flood risk outside the SFHA is often underestimated because of minimal flood-related insurance requirements and regulations and sparse flood depth data. This study proposes a systematic approach to predict flood risk for a single-family home using average annual loss (AAL) in the shaded X Zone–the area immediately outside the SFHA (i.e., the 500-year floodplain), which lies between the limits of the 1.0- and 0.2-percent annual flood probability. To further …

Feasible Delivery System Based On Poly(Lactictide-Co-Glycolide) Nanoparticles Loaded With Antimicrobial Mupirocin For Possible Wound Healing, Ludmila Košarišťanová, Tomáš Komprda, Vendula Popelková, Tatiana Fialová, Pavla Vymazalová, Carlos E. Astete

Faculty Publications

The objective of the study was to assess cytotoxicity (based on the dimethylthiazol– diphenyltetrazolium bromide cell viability assay) and antimicrobial effects of poly(lactictide-co-glycolide) nanoparticles with entrapped mupirocin (PLGA/MUP NPs) on Staphylococcus aureus and methicillin-resistant S. aureus (MRSA) strains using a disk-diffusion method, cryo-scanning electron microscopy (cryo-SEM) and fluorescence microscopy. Based on the evaluation of the growth curve, PLGA/MUP NPs inhibited growth of the both tested strains already at a concentration of 0.29 µg/ml, and their inhibitory effect at concentrations from 0.29 to 1.17 µg/ml was comparable with free MUP using the disk-diffusion method. PLGA/MUP NPs also tended to increase the …

Gcs Site Selection In Saline Miocene Formations In South Louisiana, Muhammad Zulqarnain, Stephen O. Sears, Mehdi Zeidouni, Richard G. Hughes, Douglas Carlson, Carlos F. Rivera

Faculty Publications

One of the key requirements of a commercial scale geologic carbon sequestration (GCS) site selection process is identifying injection sites to safely inject and retain injected CO2 over extended time scales. This requires thorough evaluation of site-specific surface and subsurface features. A site screening and selection framework was developed and used to identify potential sites in South Louisiana, incorporating surface data including site proximity to large CO2 stationary sources, vicinity of large population centres and state lands, land usage, legacy oil and gas wells, and local/regional geologic trends. Regionally the Miocene sediments thicken and dip towards the south, reflecting a …

Resonant Perfect Absorption Yielded By Zero-Area Pulses, Yu He, Zuoye Liu, Christian Ott, Adrian N. Pfeiffer, Shaohua Sun, Mette B. Gaarde, Thomas Pfeifer, Bitao Hu

Faculty Publications

We propose and study the manipulation of the macroscopic transient absorption of an ensemble of open two-level systems via temporal engineering. The key idea is to impose an ultrashort temporal gate on the polarization decay of the system by transient absorption spectroscopy, thus confining its free evolution and the natural reshaping of the excitation pulse. The numerical and analytical results demonstrate that even at moderate optical depths, the resonant absorption of light can be reduced or significantly enhanced by more than 5 orders of magnitude relative to that without laser manipulation. The achievement of the quasicomplete extinction of light at …

Light-Weight Structural Optimization Through Biomimicry, Machine Learning, And Inverse Design, Adithya Challapalli

LSU Doctoral Dissertations

In load-bearing lightweight architectures, cellular materials were frequently utilized. While octahedron, tetrahedron, and octet truss lattice truss were built for lightweight architectures with stretching and flexural dominance, it can be believed that new cells could easily be designed that might perform much better than the present ones in terms of mechanical and architectural characteristics. Machine learning-based structure scouting and design improvisation for better mechanical performance is a growing field of study. Additionally, biomimicry—the science of imitating nature’s elements—offers people a wealth of resources from which to draw motivation as they work to create a better quality of life.

Here, utilizing …

Research Gaps And Opportunities In Precision Nutrition: An Nih Workshop Report, Bruce Y. Lee, José M. Ordovás, Elizabeth J. Parks, Cheryl A.M. Anderson, Albert László Barabási, Steven K. Clinton, Kayla De La Haye, Valerie B. Duffy, Paul W. Franks, Elizabeth M. Ginexi, Kristian J. Hammond, Erin C. Hanlon, Michael Hittle, Emily Ho, Abigail L. Horn, Richard S. Isaacson, Patricia L. Mabry, Susan Malone, Corby K. Martin, Josiemer Mattei, Simin Nikbin Meydani, Lorene M. Nelson, Marian L. Neuhouser, Brendan Parent, Nicolaas P. Pronk, Helen M. Roche, Suchi Saria, Frank A.J.L. Scheer, Eran Segal, Mary Ann Sevick, Tim D. Spector, Linda Van Horn, Krista A. Varady, Venkata Saroja Voruganti

Clinical Research Faculty Publications

Precision nutrition is an emerging concept that aims to develop nutrition recommendations tailored to different people's circumstances and biological characteristics. Responses to dietary change and the resulting health outcomes from consuming different diets may vary significantly between people based on interactions between their genetic backgrounds, physiology, microbiome, underlying health status, behaviors, social influences, and environmental exposures. On 11-12 January 2021, the National Institutes of Health convened a workshop entitled "Precision Nutrition: Research Gaps and Opportunities" to bring together experts to discuss the issues involved in better understanding and addressing precision nutrition. The workshop proceeded in 3 parts: part I covered …

Application Of Distributed Fiber-Optic Sensing For Pressure Predictions And Multiphase Flow Characterization, Gerald Kelechi Ekechukwu

LSU Doctoral Dissertations

In the oil and gas industry, distributed fiber optics sensing (DFOS) has the potential to revolutionize well and reservoir surveillance applications. Using fiber optic sensors is becoming increasingly common because of its chemically passive and non-magnetic interference properties, the possibility of flexible installations that could be behind the casing, on the tubing, or run on wireline, as well as the potential for densely distributed measurements along the entire length of the fiber. The main objectives of my research are to develop and demonstrate novel signal processing and machine learning computational techniques and workflows on DFOS data for a variety of …

Scientometric Mapping Of Global Research On Green Retrofitting Of Existing Buildings (Greb): Pathway Towards A Holistic Greb Framework, Mershack O. Tetteh, Amos Darko, Albert P.C. Chan, Amirhosein Jafari, Ioannis Brilakis, Weiwei Chen, Gabriel Nani, Sitsofe Kwame Yevu

Faculty Publications

Green retrofitting of existing buildings (GREB) represents one of the best opportunities to reduce global energy consumption and carbon emissions, as well as improve people's health, well-being, and quality of life. It has thus received significant attention from researchers and practitioners over the years, with the proliferation of research works and publications. However, no study has attempted to comprehensively investigate the cumulative theoretical and practical value of this body of knowledge. This study aims to analyze the existing global research on GREB through the lens of a scientometric review technique and to provide pathways for future research. The scientometric mapping …

A Very Luminous Jet From The Disruption Of A Star By A Massive Black Hole, Igor Andreoni, Michael W. Coughlin, Daniel A. Perley, Yuhan Yao, Wenbin Lu, S. Bradley Cenko, Harsh Kumar, Shreya Anand, Anna Y.Q. Ho, Mansi M. Kasliwal, Antonio De Ugarte Postigo, Ana Sagués-Carracedo, Steve Schulze, D. Alexander Kann, S. R. Kulkarni, Jesper Sollerman, Nial Tanvir, Armin Rest, Luca Izzo, Jean J. Somalwar, David L. Kaplan, Tomás Ahumada, G. C. Anupama, Katie Auchettl, Sudhanshu Barway, Eric C. Bellm, Varun Bhalerao, Joshua S. Bloom, Michael Bremer, Mattia Bulla, Eric Burns, Sergio Campana, Poonam Chandra

Faculty Publications

Tidal disruption events (TDEs) are bursts of electromagnetic energy that are released when supermassive black holes at the centres of galaxies violently disrupt a star that passes too close¹. TDEs provide a window through which to study accretion onto supermassive black holes; in some rare cases, this accretion leads to launching of a relativistic jet^2–9, but the necessary conditions are not fully understood. The best-studied jetted TDE so far is Swift J1644+57, which was discovered in γ-rays, but was too obscured by dust to be seen at optical wavelengths. Here we report the optical detection of …

Few-Shot Specific Emitter Identification Via Deep Metric Ensemble Learning, Yu Wang, Guan Gui, Yun Lin, Hsiao Chun Wu, Chau Yuen, Fumiyuki Adachi

Faculty Publications

Specific emitter identification (SEI) is a highly potential technology for physical-layer authentication that is one of the most critical supplements for the upper-layer authentication. SEI is based on radio frequency (RF) features from circuit difference, rather than cryptography. These features are inherent characteristics of hardware circuits, which are difficult to counterfeit. Recently, various deep learning (DL)-based conventional SEI methods have been proposed, and achieved advanced performances. However, these methods are proposed for close-set scenarios with massive RF signal samples for training, and they generally have poor performance under the condition of limited training samples. Thus, we focus on few-shot SEI …

Pnp Maxtools: Autonomous Parameter Control In Maxmsp Utilizing Mir Algorithms, Austin Alexander Franklin

LSU Doctoral Dissertations

This research presents a new approach to computer automation through the implementation of novel real-time music information retrieval algorithms developed for this project. It documents the development of the PnP.Maxtools package, a set of open source objects designed within the popular programming environment MaxMSP. The package is a set of pre/post processing filters, objective and subjective timbral descriptors, audio effects, and other objects that are designed to be used together to compose music or improvise without the use of external controllers or hardware. The PnP.Maxtools package objects are designed to be used quickly and easily using a `plug and play' …

Leveraging Critical Information Literacy To Develop Social Justice-Minded Data Literacy Competencies, Ben B. Chiewphasa, Matthew L. Sisk

Journal of Critical Digital Librarianship

Librarians who interact with data in different contexts can come together in a community of practice – leveraging each other's perspectives to collectively engage with critical librarianship and reimagine social justice-related learning outcomes for information and data literacy programming. Specifically, this paper explores the overlapping goals of different critical literacies (such as critical information literacy and QuantCrit), showcasing that synergies exist between social justice-oriented librarians with distinctive roles and responsibilities. By leveraging a community of practice as a vehicle for continuing education in inclusive pedagogy, librarians can empower their patrons, students, and colleagues to challenge and act upon surrounding data …

Using Solar Radiation Data In Soil Moisture Diagnostic Equation For Estimating Root-Zone Soil Moisture, Olumide Omotere, Feifei Pan, Lei Wang

Faculty Publications

The soil moisture daily diagnostic equation (SMDE) evaluates the relationship between the loss function coefficient and the summation of the weighted average of precipitation. The loss function coefficient uses the day of the year (DOY) to approximate the seasonal changes in soil moisture loss for a given location. Solar radiation is the source of the energy that drives the complex and intricates of the earth-atmospheric processes and biogeochemical cycles in the environment. Previous research assumed DOY is the approximation of other environmental factors (e.g., temperature, wind speed, solar radiation). In this article, two solar radiation parameters were introduced, i.e., the …

Switching Between Topological Edge States In Plasmonic Systems Using Phase-Change Materials, Yin Huang, Yuecheng Shen, Georgios Veronis

Faculty Publications

We introduce non-Hermitian plasmonic waveguide-cavity structures based on the Aubry-Andre-Harper model to realize switching between right and left topological edge states (TESs) using the phase-change material Ge2Sb2Te5 (GST). We show that switching between the crystalline and amorphous phases of GST leads to a shift of the dispersion relation of the optimized structure so that a right TES for the crystalline phase, and a left TES for the amorphous phase occur at the same frequency. Thus, we realize switching between right and left TESs at that frequency by switching between the crystalline and amorphous phases of GST. Our results could be …

Photo-Crosslinkable And Ultrastable Poly(1,4-Butadiene) Based Organogel With Record-High Reversible Elongation Upon Cooling And Contraction Upon Heating, Xiaming Feng, Guoqiang Li

Faculty Publications

Two-way shape memory polymers with reversible elongation upon cooling (EUC) and contraction upon heating (CUH) have emerged as promising smart materials for use in soft actuators. However, it remains challenging to develop organogels with as high as possible actuation strain. Here, novel photo-crosslinkable poly(1,4-butadiene) (PBD) based organogels with exceptional stability and high reversible EUC and CUH have been developed for the first time. The conventional photo-initiator 2-hydroxy-2-methylpropiophenone and plasticizer bis(2-ethylhexyl) phthalate were utilized to achieve photo-crosslinking ability and to serve as the organic free phase, respectively. Owing to the stability of the plasticizer, the PBD based organogels are pretty stable …

Programming The Properties Of Branched Polymers Through Precision Architectures, Michael R. Dearman

LSU Master's Theses

The glass transition of branched polymers is determined by multiple structural parameters that dictate their inter- and intramolecular interactions, and ultimately, their molecular packing in the amorphous phase. Here we examined the impact of side chain length, backbone length, molecular weight composition, and topology on the glass transition behavior of bottlebrush polymers. Through examining precision bottlebrush polymer libraries (PBP, ĐSC = 1.0), we find the infinite molecular weight Tg is reached at a specific brush length after which the effect of the side-chain length dominates. Being a factor more dominant than the backbone, side-chain length affects the Tg of bottlebrush …

A Predictive Model Using The Mesoscopic Architecture Of The Living Brain To Detect Alzheimer’S Disease, Marianna Inglese, Neva Patel, Kristofer Linton-Reid, Flavia Loreto, Zarni Win, Richard J. Perry, Christopher Carswell, Matthew Grech-Sollars, William R. Crum, Haonan Lu, Paresh A. Malhotra, Lisa C. Silbert, Betty Lind, Rachel Crissey, Jeffrey A. Kaye, Raina Carter, Sara Dolen, Joseph Quinn, Lon S. Schneider, Sonia Pawluczyk, Mauricio Becerra, Liberty Teodoro, Karen Dagerman, Bryan M. Spann, James Brewer, Helen Vanderswag, Adam Fleisher, Jaimie Ziolkowski, Judith L. Heidebrink, Zbizek-Nulph, Joanne L. Lord, Lisa Zbizek-Nulph, Ronald Petersen, Sara S. Mason

Clinical Research Faculty Publications

Background: Alzheimer’s disease, the most common cause of dementia, causes a progressive and irreversible deterioration of cognition that can sometimes be difficult to diagnose, leading to suboptimal patient care. Methods: We developed a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted MRI scans, with or without cognitive scores. For each patient, a biomarker called “Alzheimer’s Predictive Vector” (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO). Results: The ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer’s related pathologies (98% and 81% accuracy between ADrp - including the early form, mild …