Digital Commons Network^™

From Pixels To Patterns: Coupling Optical Coherence Tomography And Machine Learning For Monitoring Coastal Wetland Root Systems, Mohamed O. Hassan, Aramy Truong, Maruti Mudunuru, Leslie G. Butler, Andre Rovai, Curtis Larimer, Joseph Daddona, Amir Ahkami, Jay Bardhan, Tamas Varga, Kelly Stratton, Satish Karra, Robert Twilley, Navid H. Jafari

Faculty Publications

Coastal wetlands are crucial in shoreline stabilization, carbon sequestration, and storm protection. Yet, due to limitations in traditional destructive sampling techniques, the belowground biomass (live root mass) and necromass (dead and decaying roots) remain difficult to assess in coastal wetlands, limiting our understanding on coastal resilience, nutrient cycling, and soil structure. This study employs Optical Coherence Tomography (OCT) as a high-resolution imaging technique to analyze root biomass and necromass in the Terrebonne Basin, Louisiana. A Random Forest (RF) model was developed to classify root health conditions based on OCT-derived features, achieving an accuracy of 70 % in distinguishing live from …

Intrinsic Defects (Vacancies And Antisites) In Neutron Irradiated Cdsip2 Crystals, Timothy D. Gustafson, Elizabeth M. Scherrer, Nancy C. Giles, Kevin T. Zawilski, Peter G. Schunemann, Jonathan E. Slagle, Kent L. Averett, Larry E. Halliburton

Faculty Publications

Cadmium silicon phosphide (CdSiP₂) is a nonlinear optical material widely used in optical parametric oscillators. Intrinsic defects (vacancies and antisites) are responsible for unwanted broad optical absorption bands in these crystals that degrade the performance of the devices. In the present work, optical absorption and electron paramagnetic resonance (EPR) spectra are acquired (at room temperature and 12 K, respectively) from a neutron-irradiated CdSiP₂ crystal. After the irradiation, the crystal is highly absorbing from the band edge near 600 nm to beyond 1.3 μm because of overlapping defect-related absorption bands. Heating to 550 °C removes nearly all the …

A Comprehensive Assessment And Benchmark Studyof Large Atomistic Foundation Models For Phonons, Md Zaibul Anam, Ogheneyoma Aghoghovbia, Mohammed Al-Fahdi, Lingyu Kong, Victor Fung, Ming Hu

Faculty Publications

The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces. While their capability for modeling phonon properties is emerging, systematic benchmarking across chemically diverse systems remains limited. We evaluate six recent uMLPs—EquiformerV2, MatterSim, MACE, and CHGNet—on 2429 crystalline materials from the Open Quantum Materials Database. Models were used to compute atomic forces in displaced supercells, derive interatomic force constants (IFCs), and predict phonon properties including lattice thermal conductivity (LTC), compared with density functional theory and experimental data. The EquiformerV2 pretrained model trained on the OMat24 dataset exhibits strong …

Evaluating Platinum, Gold, Glassy Carbon, And Graphite Anodes For Chlorine Evolution In Molten Calcium Chloride Salt, Cameron Vann, Shelssie Klvacek, Carlos Mejia, Devin Rappleye

Faculty Publications

The chlorine evolution reaction (CER) in molten CaCl₂ plays a critical role in high-temperature electrochemical processes, including chlorination, metal refining, and used nuclear fuel treatment. This study evaluates the performance of gold (Au), platinum (Pt), glassy carbon (GC), and graphite anodes for the CER under consistent electrochemical conditions. Anode performance was assessed based on chlorine (Cl₂) gas evolution, material robustness, and kinetic parameters. Cl₂ generation was directly confirmed using quadrupole mass spectrometry for Pt, GC, and graphite anodes. GC and graphite demonstrated stable and sustained CER activity. Pt and Au were shown to have significant mass …

Multimodal Reprogramming Of The Tumor Microenvironment By Mmr And Dual Checkpoint Blockade In Hepatocellular Carcinoma Models, Mulu Z. Tesfay, Aleksandra Cios, Khandoker Usran Ferdous, Randal S. Shelton, Bahaa Mustafa, Camila C. Simoes, Murat Gokden, Isabelle R. Miousse, Kimberly J. Krager, Marjan Boerma, Alicja Urbaniak, Anuradha Kunthur, Sri Obulareddy, Joshua M. Eichhorn, Steven R. Post, Jean Christopher Chamcheu, Omeed Moaven, Chiswili Y. Chabu, Dan G. Duda, Matteo Conti, Bruno Nardo, Rang Govindarajan, Martin E. Fernandez-Zapico, Lewis R. Roberts, Mitesh J. Borad, Martin J. Cannon, Alexei G. Basnakian, Bolni M. Nagalo

Faculty Publications

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, thus, there is an urgent need to develop more effective therapeutic options for this dismal condition. Tumor-infiltrating lymphocytes (TILs) are associated with improved response to immune checkpoint blockade in HCC, but their low abundance in most cases limits their therapeutic efficacy. Here, we demonstrate, in mice, that low-dose intratumoral immunovirotherapy with the trivalent measles, mumps, and rubella vaccine (MMR) induces superior tumor-growth delay and extended host survival compared to individually administered vaccines for measles, mumps, or rubella viruses. Further, our results show that MMR therapy synergizes with PD-1 and …

Using Serial Open Circuit Potentiometry To Study Ce And Gd Deposition In Molten Licl-Kcl Eutectic, Ranon G. Fuller, Guy L. Fredrickson, Devin Rappleye

Faculty Publications

The ability to electrochemically separate individual species in a pyrochemical reprocessing salt relies on first being able to detect a separation in their reaction potentials. This requires the ability to measure reaction potentials with extreme precision. In this work, we introduce a novel technique called serial open circuit potentiometry (SOCP) and demonstrate its effectiveness at precisely measuring metal deposition reaction potentials. SOCP has several advantages over traditional open circuit potentiometry, including its abilities to quantify the error of measured equilibrium potentials by averaging many individual OCP measurements, determine overpotential deposition nucleation potentials to instrument precision, and simultaneously determine the nucleation …

Moving Beyond Traditional Legal Scholarship Impact Rankings, John Cannan

Faculty Publications

Legal academia is likely stuck with law faculty scholarly impact rankings—that is, using citation counts to judge a law faculty’s reputation and influence. But why can’t we produce better, more useful studies? Current rankings rely on outdated methods. Moreover, these rankings—touted by their creators as objective—suffer from long-standing flaws. They are also grounded in limited understandings of legal citations as sources of information. This paper calls on law librarians to advance legal citation research by adopting methodologies from other information sciences and developing legal citation taxonomies and theories.

Pathlength, Altitude And Angle Of Incidence Dependence Of Remote Water Raman Scattering, Whitney E. Schuler, Paige K. Williams, Zechariah B. Kitzhaber, Caitlyn M. English, Tammi L. Richardson, Nikos Vitzilaios, Michael L. Myrick

Faculty Publications

A small remote Raman sensor was used to measure the Raman scattering signal from clear, still water as a function of water depth (12 cm and 396 cm depth), sensor distance above the water surface (20–300 cm), and angle of incidence (0–80°) to the normal of the water surface. Under thick- and thin-sample conditions, the signal depends on either the inverse, or the inverse square, of sensor distance from the water surface, respectively. A model is derived that fits data for different sensor distances, water depths, and angles of incidence. Fits to the measured data are consistent with the known …

Detecting Polar Ring Galaxies Via Deep Learning, Fawad Kirmani, Anathavishnu S. Unnii, Varsha P. Kulkarni, Kyle Lackey, John R. Rose

Faculty Publications

Polar ring galaxies (PRGs) are peculiar galaxies that show a ring of stars, gas, and dust oriented roughly over the poles of the central ‘host’ galaxy (i.e. roughly orthogonal to the disc of the host galaxy). The formation models for these rings involve mergers or tidal interactions of the host galaxy with another galaxy. Although the identified PRGs look different from each other, they all have a ring that is not in the same plane as the disc of the host galaxy. Unlike in galaxies such as our Milky Way, where stars form in spiral arms, the rings exemplify an …

The Increase In Global Ocean Heat Content And Favorable Conditions For Tropical Cyclone And Cyclop Intensification: Accounting For El Niño, Robert Keenan Forney, Paul W. Miller, Travis A. Smith

Faculty Publications

The ocean heat content (“OHC”)—the heat energy within the ocean integrated to a reference depth—has physical drivers spanning spatial and temporal scales, including seasonality, the El Niño/Southern Oscillation (ENSO), and others. The present article investigates changes in the OHC100 during the period 1994–2020 using GLORYS12 monthly averaged ocean reanalysis. OHC100–ENSO correlation patterns are explored to glean insights about the oceanic mechanisms that facilitate the ENSO’s global teleconnections. After extracting known seasonality and ENSO signals using the Oceanic Niño Index (ONI), the OHC100 residual is analyzed to investigate multidecadal drivers of the OHC100. Lagged ENSO–OHC100 correlations (±12 months) reveal basin-scale oscillations …

The Art Of Ai Prompting In Law And Dispute Resolution Practice, John Lande

Faculty Publications

This short article offers a practical guide for using AI tools to improve the judgment and efficiency of lawyers, mediators, and arbitrators.  It cites ABA Ethics Opinion 512, which describes lawyers’ ethical duty of technological competence under the ABA Model Rules.

The article encourages practitioners to begin by selecting AI tools appropriate to their tasks such as general-purpose platforms or specialized tools listed in the article.  It explains how to write effective prompts, use follow-up questions to refine outputs, and apply professional judgment when reviewing results.  It includes a list of suggested follow-up prompts.

Getting useful results from AI tools …

Real-Time Electron Spectrometer Utilizing A Permanent Magnet And Diode Detector Array, Mason W. Heath, Kenneth L. Matthews, Garrett M. Pitcher, Kenneth R. Hogstrom

Faculty Publications

Background: Magnetic spectrometers have been previously described for measuring energy spectra of therapeutic electron beams. However, challenges for clinical utilization have been their size, weight, and limited real-time capabilities. Development of a compact, lightweight, and inexpensive device with real-time readout will make an electron spectrometer a practical clinical tool. Purpose: This work integrates a commercial diode detector array with a permanent dipole magnet to create a practical real-time energy spectrometer for therapeutic electron beams. Methods: A 4 kg, 0.55 T permanent dipole magnet was coupled to two PC boards of a Sun Nuclear SRS MapCHECK device, which provided two interlaced …

Attribution As Architecture In The Digital Age, Laura A. Heymann

Faculty Publications

As technology changes, one thing remains constant: human creators seem to care about attribution, whether as creators or as audience members. Current U.S. law lacks the means for many creators to effectively address attributional interests, and experience has shown that top-down, imposed technological solutions can fail to gain the necessary buy-in and adoption. The best approach, examples suggest, is for platforms to think of attribution as part of the architecture of their systems, but to take their cues from user-developed, individualized solutions, which will not only be more responsive to user interests but also allow adaptation as interests change and …

Better Digital Contracts With Prosocial Friction-In-Design, Brett Frischmann, Moshe Y. Vardi

Faculty Publications

Contract law is supposed to enable people to reach genuine agreements and cooperate. If this ideal was ever a reality, the rise of mass market contracts and boil­erplate rendered it pure fiction. Modern consumer contracts are incomprehensible to most people. No one reads them anyway.

Digital contracting involves design features that amplify traditional boilerplate harms and create others. For example, digital contracting is too cheap; low marginal costs lead to overexpansion in scale and scope. To make matters worse, the loss of autonomy from repeat engagement with digital contracting systems is pernicious. People become increasingly predictable and programmable as digital …

Integration Of Sco2 Brayton Cycles With Carbon Capture Systems, Nathan C. Stearns, Rajarshi Roy, Brian Schooff, Andrew Chiodo, Andrew R. Fry, Brian D. Iverson

Faculty Publications

Increasing global energy consumption and greater market penetration of intermittent energy sources require a baseline power source to enable renewable energies. Here, a case is made for pairing supercritical CO₂ Brayton cycles with carbon capture to create low-emission, high-efficiency, combustion-based power generation systems. Pairing carbon capture and storage (CCS) systems with supercritical carbon dioxide (sCO₂) Brayton cycles enables the reduction of greenhouse gas emissions in combustion systems, but with an associated energy cost. Three different representative models of CCS systems (oxyfuel combustion, amine scrubbing, and cryogenic carbon capture) are considered for pairing with an sCO2 Brayton cycle, …

Polymorphism Crystal Structure Prediction With Adaptive Space Group Diversity Control, Sadman Saadeed Omee, Lai Wei, Jianjun Hu

Faculty Publications

Crystalline materials can form different structural arrangements (i.e., polymorphs) with the same chemical composition, exhibiting distinct physical properties depending on how they are synthesized or the conditions under which they operate. For example, carbon can exist as graphite (soft, conductive) or diamond (hard, insulating). Computational methods that can predict these polymorphs are vital in materials science, which help understand stability relationships, guide synthesis efforts, and discover new materials with desired properties without extensive trial-and-error experimentation. However, effective crystal structure prediction (CSP) algorithms for inorganic polymorph structures remain limited. ParetoCSP2 is proposed, a multi-objective genetic algorithm for polymorphism CSP that incorporates …

An Event-Based Time-Incremented Snn Architecture Supporting Energy-Efficient Device Classification, David L. Weathers, Michael A. Temple, Brett J. Borghetti

Faculty Publications

Recent advances in Radio Frequency (RF)-based device classification have shown promise in enabling secure and efficient wireless communications. However, the energy efficiency and low-latency processing capabilities of neuromorphic computing have yet to be fully leveraged in this domain. This paper is a first step toward enabling an end-to-end neuromorphic system for RF device classification, specifically supporting development of a neuromorphic classifier that enforces temporal causality without requiring non-neuromorphic classifier pre-training. This Spiking Neural Network (SNN) classifier streamlines the development of an end-to-end neuromorphic device classification system, further expanding the energy efficiency gains of neuromorphic processing to the realm of RF …

Dilute Magnetic Impurity-Induced Effective Phonon Magnetic Moment In Fe-Doped Monolayer Mos2, Hussam Mustafa, Gaihua Ye, Cynthia Nnokwe, Mengqi Fang, Mohamed Kandil, Abdullah Al-Mahboob, Kai Wu, Andrew James Stollenwerk, Timothy E. Kidd, Paul M. Shand, Jerzy T. Sadowski, Eui Hyeok Yang, Yinong Zhou, Rui He, Wencan Jin

Faculty Publications

Realization of large effective phonon magnetic moment in monolayer MoS2 has established an important route for exploring intriguing magnetic phenomena in a nonmagnetic material. The sizable coupling between the orbital transition and the circularly polarized phonon results in the large effective phonon magnetic moment. In this work, using magneto-Raman spectroscopy, we investigate substitutional doping of magnetic atoms as a tuning knob of the electronic and phononic properties of MoS2. We show that Fe-doping polarizes the spin of the conduction bands and introduces a localized Fe band underneath the conduction band. As a result, an additional orbital transition between the Mo …

Machine-Learning-Assisted Discovery Of Lattice Dynamics Signatures Of Sodium Superionic Conductors, Ogheneyoma Aghoghovbia, Riccardo Rurali, Mohammed Al-Fahdi, Joshua Ojih, De-En Jiang, Ming Hu

Faculty Publications

Sodium superionic conductors are key to the development of all-solid-state sodium batteries. Discovery of new superionic conductors has traditionally relied on insights from material defect chemistry and the transition/hopping theory, while the role of lattice vibrations, i.e., phonons, remains underexplored. We identify key lattice dynamics signatures that govern ionic conductivity by analyzing the phonon mean squared displacement (MSD) of Na+ ions. By high-throughput screening of a dataset of 3903 Na-containing structures, we establish a strong positive correlation between phonon MSD and diffusion coefficients, providing a quantitative correlation between lattice dynamics and ion transport. To accelerate this discovery, we incorporate …

Microarchitectural Malware Detection Via Translation Lookaside Buffer (Tlb) Events, Cristian Agredo, Daniel F. Koranek, Christine M. Schubert Kabban, Jose R. Gutierrez Del Arroyo, Scott R. Graham

Faculty Publications

Prior work has shown that Translation Lookaside Buffer (TLB) data contains valuable behavioral information. Many existing methodologies rely on timing features or focus solely on workload classification. In this study, we propose a novel approach to malware classification using only TLB-related Hardware Performance Counters (HPCs), explicitly excluding any dependence on timing features such as task execution duration or memory access timing. Our methodology evaluates whether TLB data alone, without any timing information, can effectively distinguish between malicious and benign programs. We test this across three classification scenarios: (1) A binary classification problem involving distinguishing malicious from benign tasks, (2) a …

Occulation Observations With Event-Based Vision Sensors [ Poster ], Rachel Oliver, Paul Rickerhauser, Brian Mcreynolds

Faculty Publications

Event-based vision sensors (EVS) offer exceptional change detection capabilities due to their asynchronous and independent pixels which record binary events with changes in their photocurrent. The resulting address event representation data is a sparse timeseries list.

Fluorinated Electrolytes For Lithium–Sulfur And Beyond-Lithium Metal–Sulfur Batteries, Avinash Raulo, Saheed Lateef, Hunter Mcray, Kaushek Rahul Ilancheran, Fabio Albano, Golareh Jalilvand

Faculty Publications

Metal–sulfur batteries, particularly lithium–sulfur (Li–S) systems, have attracted significant attention due to their high theoretical energy densities, low cost, and sustainability benefits arising from sulfur’s abundance and non-toxicity. Despite extensive research, their practical deployment remains limited by persistent challenges such as polysulfide shuttling and metal anode degradation, which collectively lead to poor coulombic efficiency and limited cycle life. These issues are further intensified in emerging systems employing sodium, potassium, magnesium, calcium, and siliconbased anodes. Fluorinated electrolytes have emerged as a promising approach to address these limitations. Fluorination enhances oxidative stability, suppresses polysulfide dissolution, promotes stable solid–electrolyte interphase (SEI) formation, and …

Wave Intensity Analysis With Exercise Identifies Impairments In Pulmonary Hypertension, Christopher G. Lechuga, Farhan Raza, Mitchel J. Colebank, Claudia E. Korcarz, Jens C. Eickhoff, Naomi C. Chesler

Faculty Publications

Wave intensity analysis provides a novel approach to understanding the dynamic interactions between the right ventricle and pulmonary vasculature, particularly in pulmonary hypertension, a condition characterized by elevated pulmonary arterial pressures and vascular remodeling. This prospective study used wave intensity analysis to evaluate right ventricular and pulmonary vascular mechanics in 22 participants with pulmonary hypertension (including precapillary, isolated postcapillary, and combined pre/postcapillary pulmonary hypertension), and three without pulmonary hypertension. Forward and backward compression and decompression waves were quantified at rest and during incremental exercise (25, 50, and 75 W). Relationships between metrics of wave intensity analysis, hemodynamics, right ventricular function, …

Resolution Of Physics And Deep Learning-Based Protein Engineering Filters: A Case Study With A Lipase For Industrial Substrate Hydrolysis, Spencer Gardiner, Peter Dollinger, Filip Kovacic, Jörge Pietruszka, Daniel Ess, Karl-Erich Jaeger, Gunnar F. Schröder, Dennis Della Corte

Faculty Publications

Computational enzyme design remains a powerful yet imperfect tool for optimizing biocatalysts, especially when targeting non-natural substrates. Using design tools we investigated Pseudomonas aeruginosa LipA, a lipase with a flexible lid domain crucial for substrate binding and turnover, aiming to enhance its hydrolysis of the industrially relevant substrate Roche ester. We generated an initial set of single-point mutations based on structural proximity to the active site and evaluated their effects using a computational pipeline integrating molecular dynamics (MD) simulations, density functional theory (DFT) calculations, and ensemble-based energy scoring. While we identified several active variants, attempts to rank them by activity …

Profit Shifting And The States: A Short Primer, David Gamage

Faculty Publications

This essay argues that corporate profit shifting remains one of the most significant challenges for U.S. state tax systems. Multinational enterprises continue to shift billions in profits to offshore tax havens, eroding state tax bases, distorting market competition, and forcing a greater reliance on more regressive taxes. We contend that the dominant "water's-edge" combined reporting method used by most states is structurally inadequate to combat modern profit-shifting techniques, which primarily involve the manipulation of intangible assets. The recent transformation of federal tax law (from GILTI to NCTI) and the global adoption of the OECD's Pillar 2 minimum tax framework create …

Event-Based Sensor Noise Modeling For Space-Based Space Domain Awareness, Rachel Oliver, Brian Mcreynolds, Dmitry Savransky

Faculty Publications

Building off the foundation of a physics-based end-to-end model for event-based vision sensors (EVS) observing resident space objects (RSOs), we apply new techniques to model realistic low-light sensor noise. While previous approaches simulate memorized current leakage and apply temporal noise models, our methods improve on these approaches and additionally account for current-following noise as an event source. These improvements are key components for accurate event-generating simulators which can advise requirements and concepts of operations for dedicated event-based Space Domain Awareness (SDA) architectures. The EVS pixel’s independent and asynchronous recording of changes in photocurrent produces data with high temporal resolution and …

A C++ Library For Turbulent Mixing Simulation Using Hierarchical Parcel Swapping (Hips), Masoomeh Behrang, Tommy Starick, Heiko Schmidt, David O. Lignell

Faculty Publications

Turbulence models are crucial for simulating flows at all scales, capturing both large-scale structures and small-scale mixing. Software libraries that implement such models should support modular integration, customization, and scalability across different simulation frameworks. This paper presents Hierarchical Parcel Swapping (HiPS), a C++ library documented with Doxygen and available on GitHub. HiPS supports both mixing and reactions and can be used as a standalone model or as a subgrid model in CFD simulations. The code includes examples for users to run it as a standalone model. Additionally, considerations for using it as a subgrid model are provided.

Analyzing Lf/Vlf Lightning Waveforms To Estimate D-Region Electron Density Profiles, William R. Smith, Erin H. Lay, Kyle E. Fitch, Daniel J. Emmons

Faculty Publications

Lightning waveforms in the low frequency (LF; 30–300 kHz) and the very low frequency (VLF; 3–30 kHz) bands can be exploited to produce data-driven ionospheric D-region electron density profile (EDP) estimates with significantly higher spatial and temporal coverage than previously available. The lightning waveforms used in this paper are signals detected in the LF/VLF of negative cloud-to-ground lightning by the Earth Networks Total Lightning Detection Network. Each waveform contains a ground wave and a time-delayed ionospheric reflection. The time delay between the ground wave and ionospheric reflection has previously been used to estimate a single specular reflection altitude, where LF/VLF …

Magnetic Nanoparticles Tethered With Zn–Dpa For The Removal Of Bacteria From Red Blood Cell Suspension, Tochukwu P. Okonkwo, Rajendra P. Gautam, Jacob B. Limburg, Breckin L. Forstrom, Bowen J. Houser, Aaron Rappleyea, Tyler P. Green, Joseph P. Talley, Alexander D. Daum, Stacey J. Smith, Karine Chesnel, William G. Pitt, Roger G. Harrison

Faculty Publications

Bacterial infections continue to drive the need for more effective and rapid methods for bacterial analysis. To address this, magnetic nanoparticles (MNPs) have emerged as promising tools, especially when their surfaces are modified with bacteria binders. The bis-zinc–dipicolylamine (Zn–DPA) complex is known for its broad affinity to bacteria. We have synthesized MNPs via a thermal decomposition method, encapsulated them in silica, modified their surface with Zn–DPA, and tested their ability to remove bacteria. The MNPs retain their superparamagnetic properties and crystallite structure after being encapsulated. The MNPs coated with silica and Zn–DPA effectively bind and remove both Gram-positive and Gram-negative …

Time Series Changes Of Surficial Sediments On Eastern Ship Shoal, Louisiana Shelf, Adam Gartelman, Kehui Xu, Brian J. Roberts, David Samuel Johnson, Madison Liotta

Faculty Publications

Ship Shoal, a large transgressive sand body on the Louisiana continental shelf, is a critical sediment source for coastal restoration. This study evaluates spatial and temporal variability in sediment grain size, percents organic matter (%OM), and carbonate (%CO3) across the shoal crest (REF), Caminada Dredge Pit (CAM), and Terrebonne Dredge Pit (TER). Sediment samples were collected between 2020 and 2022 using box cores and analyzed for grain size, %OM, and %CO3, with temporal and spatial patterns assessed through statistical comparisons, correlation analyses, and random forest regression models. Results show that dredged areas act as sinks for fine-grained, organic-rich sediments, with …