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Articles 1 - 30 of 4103

Full-Text Articles in Physical Sciences and Mathematics

Finite Mathematics: A Course Guide, Angela West Dixon, Hillary Dosser Oct 2026

Finite Mathematics: A Course Guide, Angela West Dixon, Hillary Dosser

Faculty Publications

Finite Mathematics: A Course Guide is a supplement to Mathematics for Business and Social Sciences by Kathryn Bollinger and Vanessa Coffelt. The authors of this Course Guide, Angela Dixon and Hilary Dosser, are instructors of Mathematics at Stephen F. Austin State University in Nacogdoches, Texas. This Course Guide was developed in response to adapting MATH 1324, Finite Mathematics to a zero-cost course, using an Open Educational Resource (OER) implemented in the Fall semester of 2026. According to the Texas Higher Education Coordinating Board’s Academic Course Guide Manual (ACGM), MATH 1324 Mathematics for Business and Social Sciences concerns the application of …

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Waste Streams From Next Generation Molten Salt Reactors: The Challenge Of Creating An Insoluble Ceramic For Chloride Salt Waste, Alevtina A. Maksimova, Jake W. Amoroso, Matthew Page, Gregory Morrison, Hans Conrad Zur Loye Sep 2026

Waste Streams From Next Generation Molten Salt Reactors: The Challenge Of Creating An Insoluble Ceramic For Chloride Salt Waste, Alevtina A. Maksimova, Jake W. Amoroso, Matthew Page, Gregory Morrison, Hans Conrad Zur Loye

Faculty Publications

Molten salt reactors (MSRs) design development is of interest to many research groups and companies. Waste management for MSRs is one of the most important issues that needs to be resolved due to its impact on environmental safety, primarily via the dissolution of radionuclides in water. Furthermore, the waste treatment strategy will have a significant influence on the operating cost of MSRs, which is why a reliable process for the immobilization, transportation, storage and disposal of MSR waste must be addressed. This work presents a new approach for the immobilization of chloride salts from molten salt reactors in stable oxyhalide …

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Concepts For Supporting Indigenous And Tribal Information And Research Needs, Sharon Hausam Aug 2026

Concepts For Supporting Indigenous And Tribal Information And Research Needs, Sharon Hausam

Faculty Publications

This is a working paper produced as part of National Science Foundation project #2115169, “Transforming Rural-Urban Systems: Trajectories for Sustainability in the Intermountain West,” known as the “Intermountain West Transformation Network” (TN), led by the University of New Mexico with institutional partners at three additional universities in New Mexico, two in Arizona, and one each in Utah, Colorado, and Washington. The TN’s Indigenous and Tribal engagement was supported through a contract with Dr. Sharon Hausam, additional work by Aaron M. Canter, coordination with Dr. Lani Tsinnajinnie, and an Advisory Committee on Indigenous Information Needs primarily comprised of Indigenous representatives in …

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Effective Visibility In The Infrared Bands, Peter L. Dean-Erlander, Steven T. Fiorino, Ronald G. Driggers Aug 2026

Effective Visibility In The Infrared Bands, Peter L. Dean-Erlander, Steven T. Fiorino, Ronald G. Driggers

Faculty Publications

Visibility is an atmospheric metric for the comparison of terrestrial imaging conditions and locations. A limitation of visibility is that it is defined for the visible spectrum only, and there is no simple infrared equivalent. This study compares three reflective infrared wavebands: near-IR (NIR), shortwave IR (SWIR), and extended shortwave IR (eSWIR), to the visible band across a global set of cities to develop three rule-of-thumb functions for IR effective visibility. To accomplish this, a radiometric sensor model is combined with the Laser Environmental Effects Definition and Reference (LEEDR) software package to calculate the visibility of a black-and-white contrast target …

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The Use Of Machine Learning Models For Predicting The Dielectric Strength Of Gases, Matthew Mileski, Paul W. Groth, Timothy S. Wolfe, Adib J. Samin Aug 2026

The Use Of Machine Learning Models For Predicting The Dielectric Strength Of Gases, Matthew Mileski, Paul W. Groth, Timothy S. Wolfe, Adib J. Samin

Faculty Publications

Technological advancements in high voltage systems have pushed sulfur hexafluoride (SF6) to its operational limits. Furthermore, this gas has other drawbacks including a high liquefaction temperature and a high global warming potential. Therefore, there has been an urgent need to find alternative gases with high dielectric strength (DS). In this work, density functional theory (DFT) is used to calculate molecular descriptors that are fed into an artificial neural network (ANN) and a random forest (RF). These machine learning (ML) models are then used to predict the DS for hundreds of molecules. A finite element model (FEM) is also used to …

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An Atmospheric Optical Turbulence Structure Parameter Measurements System Based On Direct Ri Sensing Using High-Resolution Fiber-Optic Sensors, Matej Njegovec, Simon Pevec, Vedran Budinski, Boris Macuh, Melissa K. Beason, Denis Onlagic Aug 2026

An Atmospheric Optical Turbulence Structure Parameter Measurements System Based On Direct Ri Sensing Using High-Resolution Fiber-Optic Sensors, Matej Njegovec, Simon Pevec, Vedran Budinski, Boris Macuh, Melissa K. Beason, Denis Onlagic

Faculty Publications

The paper presents a method to characterize the refractive index structure parameter (Cn2) associated with optical turbulence directly. The characterization system is based on miniature, high‑resolution, all‑fiber refractive index (RI) sensors. The refractive index sensors employ open‑path, low‑finesse Fabry–Perot interferometers that are approximately 8 mm long and 200 μm in diameter. The active part of the interferometers is made of ultra‑low‑expansion glass, which eliminates the influence of thermal expansion on the refractive index measurements. The proposed refractive index sensor, operating in a differential configuration, achieved a resolution of 2×10-9 RIU using a custom‑designed spectral interrogation system …

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Modeling Formation Of Turbulent Sporadic-E Clouds Using Realistic Wind Data, Aaron M. Schinder, Kenneth S. Obenberger, Jorge L. Chau, Juan M. Urco, Matthias Clahsen, Benjamin F. Akers, Daniel J. Emmons Aug 2026

Modeling Formation Of Turbulent Sporadic-E Clouds Using Realistic Wind Data, Aaron M. Schinder, Kenneth S. Obenberger, Jorge L. Chau, Juan M. Urco, Matthias Clahsen, Benjamin F. Akers, Daniel J. Emmons

Faculty Publications

A high resolution two-dimensional multi-fluid model of sporadic-E layers was developed and driven with physically realistic mesosphere, lower thermosphere (MLT) winds measured over Albuquerque, New Mexico. The realistic E-region winds are produced by the HYdrodynamic Point-wise Environment Reconstructor (HYPER) model that ingests meteor derived wind observations from a Spread-spectrum Interferometric Multistatic meteor radar Observing Network (SIMONe) system combined with the Navier-Stokes equations to provide high resolution three-dimensional wind fields over time. Sporadic-E dynamics are simulated using both realistic winds from HYPER as well as idealized hyperbolic tangent windshears to compare and contrast. Overall, the model shows greater inhomogeneity and irregularity …

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Crystal Structure Of New Polar Rare Earth Borates Na2.62Ln2.12(Bo3)3 (Ln = Pr, Nd, Sm) Containing Isolated Bo3 Groups, Alevtina A. Maksimova, Mark D. Smith, Hans Conrad Zur Loye Aug 2026

Crystal Structure Of New Polar Rare Earth Borates Na2.62Ln2.12(Bo3)3 (Ln = Pr, Nd, Sm) Containing Isolated Bo3 Groups, Alevtina A. Maksimova, Mark D. Smith, Hans Conrad Zur Loye

Faculty Publications

Three new rare earth borates, Na2.62Ln2.12(BO3)3 (Ln = Pr, Nd, Sm), were synthesized via a high-temperature solution reaction using a BaCO3–H3BO3–NaF flux and structurally characterized by single-crystal X-ray diffraction analysis. The compounds crystallize in the orthorhombic space group Amm2 with lattice parameters a = 5.0985(10) Å, b = 11.180(2) Å, c = 7.1483(14) Å, and a unit cell volume of 407.48(14) Å3 (Z = 2) for Na2.62Pr2.12(BO3)3, a = 5.0983(10) Å, b = 11.181(2) Å, c = 7.1491(14) Å, and a unit cell volume of 407.51(14) Å3 (Z = 2) for Na2.62Nd2.12(BO3)3, and a = 5.08630(10) Å, b …

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Single Crystal Growth Of The Orthoborate Nabalu(Bo3)2 And Optical Investigation Of Eu3+ And Tb3+ Doped Nabalu(Bo3)2, Alevtina A. Maksimova, Mark D. Smith, Lakshani W. Masachchi, Hans Conrad Zur Loye Aug 2026

Single Crystal Growth Of The Orthoborate Nabalu(Bo3)2 And Optical Investigation Of Eu3+ And Tb3+ Doped Nabalu(Bo3)2, Alevtina A. Maksimova, Mark D. Smith, Lakshani W. Masachchi, Hans Conrad Zur Loye

Faculty Publications

Sodium barium lutetium borate NaBaLu(BO3)2 crystals were synthesized using a high-temperature solution method. The crystal structure of this layered orthoborate is described and corresponds to that of an extensive orthoborates family, NaBaR(BO3)2 (R = Sc, Y, Yb, Tb – Lu). NaBaLu(BO3)2 was doped by Eu3+ and Tb3+ to explore its performance as a host material and to investigate the luminescent properties of the Eu3+ and Tb3+ doped materials. The emission spectra of the NaBaLu(BO3)2:Ln (Ln = Eu, Tb) crystals are presented. The most …

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Indigenous Community Research Opportunities, Sharon Hausam, Aaron M. Canter Aug 2026

Indigenous Community Research Opportunities, Sharon Hausam, Aaron M. Canter

Faculty Publications

This is a working paper produced as part of National Science Foundation project #2115169, “Transforming Rural-Urban Systems: Trajectories for Sustainability in the Intermountain West,” known as the “Intermountain West Transformation Network” (TN), led by the University of New Mexico with institutional partners at three additional universities in New Mexico, two in Arizona, and one each in Utah, Colorado, and Washington. The TN’s Indigenous and Tribal engagement was supported through a contract with Dr. Sharon Hausam, additional work by Aaron M. Canter, coordination with Dr. Lani Tsinnajinnie, and an Advisory Committee on Indigenous Information Needs primarily comprised of Indigenous representatives in …

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Opportunities For Leadership In Indigenous And Tribally Engaged Research At The University Of New Mexico, Sharon Hausam Aug 2026

Opportunities For Leadership In Indigenous And Tribally Engaged Research At The University Of New Mexico, Sharon Hausam

Faculty Publications

This is a working paper produced as part of National Science Foundation project #2115169, “Transforming Rural-Urban Systems: Trajectories for Sustainability in the Intermountain West,” known as the “Intermountain West Transformation Network” (TN), led by the University of New Mexico with institutional partners at three additional universities in New Mexico, two in Arizona, and one each in Utah, Colorado, and Washington. The TN’s Indigenous and Tribal engagement was supported through a contract with Dr. Sharon Hausam, additional work by Aaron M. Canter, coordination with Dr. Lani Tsinnajinnie, and an Advisory Committee on Indigenous Information Needs primarily comprised of Indigenous representatives in …

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Ai-Powered Resume Screening, Sang Suh, Numery Zaber Jul 2026

Ai-Powered Resume Screening, Sang Suh, Numery Zaber

Faculty Publications

Traditional resume screening is manual, slow, and susceptible to bias, and it struggles to keep pace with today’s application volumes. This paper presents a dual-engine, AI-powered resume screening system designed for transparency and reproducibility. The primary (classical) pipeline encodes resumes and job descriptions using Sentence-BERT (SBERT), computes a resume–job match score via cosine similarity, classifies candidates into 25 job categories using XGBoost, and provides model interpretability through SHAP. In parallel, a prompted large language model (LLM) baseline (GPT-4o/4o-mini) outputs a match score and predicted category for comparative analysis. A Streamlit-based interface integrates both engines to support recruiter workflows and human-in-the-loop …

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Observations On Recurrent Loss In The Neural Network Model Of A Partial Differential Equation: The Advection–Diffusion Equation, Jonah A. Reeger Jul 2026

Observations On Recurrent Loss In The Neural Network Model Of A Partial Differential Equation: The Advection–Diffusion Equation, Jonah A. Reeger

Faculty Publications

A growing body of literature has been leveraging techniques of machine learning (ML) to build novel approaches to approximating the solutions to partial differential equations. Noticeably absent from the literature is a systematic exploration of the stability of the solutions generated by these ML approaches. Here, a recurrent network is introduced that matches precisely the evaluation of a multi-step method paired with a collocation method for approximating spatial derivatives in the advection–diffusion equation. This allows for two things: (1) the use of traditional tools for analyzing the stability of a numerical method for solving PDEs and (2) bringing to bear …

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Religious Bias In Llms Is Significantly Understudied, Sheryl Carty, Nancy Fulda, Walter Reade Jul 2026

Religious Bias In Llms Is Significantly Understudied, Sheryl Carty, Nancy Fulda, Walter Reade

Faculty Publications

In the earlier years of development of LLMs, it was relatively easy to prompt an LLM to respond with toxic or biased statements about religion. Subsequent improvements in frontier models addressed many of the issues of bias and toxicity in general, including against religion. At the same time, the adoption and usage of these models has grown exponentially. Small and implicit biases, therefore, have a magnified overall impact. In this paper, we (1) briefly review previous efforts to measure religious bias in LLMs, (2) show, by reviewing over 12,000 papers dealing with bias in LLMs, that religious bias has been …

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Comparative Analysis Of Task Scheduling In Multi-Tier Fog-Cloud Computing: From Classical Approaches To Greedy Multi-Objective Optimization, Zafril Rizal M. Azmi, Najmul Haque, Saydul Akbar Murad Jul 2026

Comparative Analysis Of Task Scheduling In Multi-Tier Fog-Cloud Computing: From Classical Approaches To Greedy Multi-Objective Optimization, Zafril Rizal M. Azmi, Najmul Haque, Saydul Akbar Murad

Faculty Publications

Fog computing extends cloud services to the network edge, enabling low-latency processing for time-sensitive applications. However, scheduling complexity significantly increases due to heterogeneous resources, dynamic workloads, and strict Quality-of-Service (QoS) constraints. Although numerous scheduling techniques have been proposed, existing studies often assess only a narrow subset of algorithms or rely on offline metaheuristics unsuitable for real-time environments. This paper presents a comprehensive comparative evaluation of twelve scheduling algorithms, including five classical, one heuristic, and six metaheuristic-inspired approaches, within a realistic 20-node multi-tier fog-cloud topology. Across 1,365 experiments spanning seven utilization levels, we analyze each algorithm’s deadline adherence, load distribution, and …

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Generation Of Khz-Rate Complex-Structured Liquid Targets For Relativistic Laser–Plasma Interactions, Michael L. Dexter, Stephen J. Hageman, Gregory Ngirmang, Kyle D. Frische, Joseph Snyder, John T. Morrison, Enam A. Chowdury, Anil K. Patnaik Jun 2026

Generation Of Khz-Rate Complex-Structured Liquid Targets For Relativistic Laser–Plasma Interactions, Michael L. Dexter, Stephen J. Hageman, Gregory Ngirmang, Kyle D. Frische, Joseph Snyder, John T. Morrison, Enam A. Chowdury, Anil K. Patnaik

Faculty Publications

With the rise of high repetition rate ultra-intense laser systems, there is a need for solid density targets to study relativistic laser–plasma interactions that can operate at the same repetition rate. Flowing liquid targets are attractive because they are self-replenished, debris free, cost effective and easy to use. Liquid targets have been used for high-repetition rate (up to kHz rate) generation of electrons, protons, x rays, and neutrons by our group and elsewhere. In this Letter, we demonstrate a kHz-rate generation of a variety of dynamically shaped complex-structured targets from the interaction of a 1016 W/cm2 focused laser …

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Analysis And Machine Learning Adaptation Of A Cognitive Model For Human Memory, Trevor Cross, Aihua W. Wood Jun 2026

Analysis And Machine Learning Adaptation Of A Cognitive Model For Human Memory, Trevor Cross, Aihua W. Wood

Faculty Publications

In this paper, we use the Duolingo SLAM dataset to analyze several cognitive models of second language acquisition and develop new approaches for enhanced performance. In particular, we consider the Predictive Performance Equation and some of its underlying power laws. Leveraging insights from machine learning, we develop simple one-feature models as building blocks for combined models that match or in certain cases outperform the existing models at much reduced computational cost. In addition, a neural network with one fully connected hidden layer is constructed that outperforms all other models on sufficiently large datasets.

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Active Learning Of Constraint Boundaries Using Expected Magnitude Of Incorrectness And Neural Networks, Atticus Beachy, Ramana V. Grandhi Jun 2026

Active Learning Of Constraint Boundaries Using Expected Magnitude Of Incorrectness And Neural Networks, Atticus Beachy, Ramana V. Grandhi

Faculty Publications

This research proposes an acquisition function for constraint boundary identification, with applications to hypersonic air vehicles. Hypersonic vehicles endure extreme thermal loads caused by aerodynamic heating, resulting in a strong coupling between structural performance and aerothermodynamics. However, modeling coupled system behaviors requires simultaneous consideration of both aerodynamic and structural design variables, increasing the dimensionality of the design trade space and the difficulty of accurately modeling the constraints. Several active learning schemes have been proposed to accelerate identification of the composite feasible region that satisfies all constraints. Some of these require integrating the surrogate model over the entire design space with …

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Main-Chain Ion-Pair Polybenzimidazole Membranes Enabling Reduced-Temperature Ht-Pemfc Operation (Down To 120°C), Brian C. Benicewicz, Huina Lin Jun 2026

Main-Chain Ion-Pair Polybenzimidazole Membranes Enabling Reduced-Temperature Ht-Pemfc Operation (Down To 120°C), Brian C. Benicewicz, Huina Lin

Faculty Publications

Proton exchange membrane (PEM) fuel cells are promising for clean and efficient energy conversion across diverse applications. High-temperature PEM fuel cells (HT-PEMFCs) using phosphoric acid (PA)-doped polybenzimidazole (PBI) can operate up to 200°C, but at lower temperatures, water-induced PA loss often leads to performance degradation and reduced durability. In this work, we present a new class of main-chain ion-pair PBI membranes by integrating the imidazolium-biphosphate ion-pair units directly into the PBI backbone. This design results in membranes with high acid content, stronger acid-polymer interactions and stabilized acid retention. In single-cell tests, the Im+-PBI15-3 wt.% exhibits peak power densities of 0.79 …

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Matching Two Long Interferometric Pathlengths Using Low Temporal Coherence Light For Finding Hong–Ou–Mandel Dip, Keith A. Wyman, Noah S. Everett, Anil K. Patnaik Jun 2026

Matching Two Long Interferometric Pathlengths Using Low Temporal Coherence Light For Finding Hong–Ou–Mandel Dip, Keith A. Wyman, Noah S. Everett, Anil K. Patnaik

Faculty Publications

Hong–Ou–Mandel (HOM) dip from a biphoton source in a two-photon interferometer provides a myriad of quantum tools for quantum communication and sensing. But the stringent requirements for spatial coherence between the photon pair makes it prohibitively difficult to observe high-fidelity HOM dip in long-distance free-space implementations, e.g., for the photon pairs involved in quantum communication need to match the two path lengths within a few 10 s of micron because of the short coherence width of the two-photon wave-packet. While many techniques for the pathlength balancing of two interferometric arms have been studied and applied extensively, such balancing is further …

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A Global Internal Tide Modeling Framework For Improving Satellite Observations Of Fine-Scale Ocean Circulation, Badarvada Yadidya, Brian K. Arbic, Edward D. Zaron, Jay F. Shriver, Maarten C. Buijsman, Eric P. Chassignet, Loren Carrère, Michel Tchilibou Jun 2026

A Global Internal Tide Modeling Framework For Improving Satellite Observations Of Fine-Scale Ocean Circulation, Badarvada Yadidya, Brian K. Arbic, Edward D. Zaron, Jay F. Shriver, Maarten C. Buijsman, Eric P. Chassignet, Loren Carrère, Michel Tchilibou

Faculty Publications

Small-scale oceanic eddies and filaments mediate the vertical exchange of heat and carbon within the global ocean. The Surface Water and Ocean Topography (SWOT) mission resolves these features through wide-swath interferometry, but internal tides often mask these observations. Non–phase-locked internal tides present special difficulty because they vary with the evolving ocean background. We show that this chaotic variability can be predicted. We use a data-assimilative ocean forecast model to resolve the mesoscale environment and separate tidal signals from the broader circulation. The model captures the organized structure of these incoherent waves in the independent SWOT measurements. Correcting for the total …

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Winddensity-Mbir: Model-Based Iterative Reconstruction For Wind Tunnel 3d Density Estimation, Karl J. Weisenburger, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz Jun 2026

Winddensity-Mbir: Model-Based Iterative Reconstruction For Wind Tunnel 3d Density Estimation, Karl J. Weisenburger, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz

Faculty Publications

Experimentalists often use wind tunnels to study aerodynamic turbulence, but most wind tunnel imaging techniques are limited in their ability to take non-invasive three-dimensional (3D) density measurements of turbulence. Wavefront tomography is a technique that uses multiple wavefront measurements from various viewing angles to non-invasively measure the 3D density field of a turbulent medium. Existing methods make strong assumptions, such as a spline basis representation, to address the ill-conditioned nature of this problem. We formulate this problem as a Bayesian, sparse-view tomographic reconstruction problem and develop a model-based iterative reconstruction algorithm for measuring the volumetric 3D density field inside a …

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Does Patient History Influence Capsular Contracture? An Exploratory Analysis With Machine Learning, Thomas M. Johnstone, Daniel Najafali, Jennifer K. Shaw, Justin M. Camacho, Chancellor Johnstone, Rahim S. Nazerali, Gordon K. Lee May 2026

Does Patient History Influence Capsular Contracture? An Exploratory Analysis With Machine Learning, Thomas M. Johnstone, Daniel Najafali, Jennifer K. Shaw, Justin M. Camacho, Chancellor Johnstone, Rahim S. Nazerali, Gordon K. Lee

Faculty Publications

Background: Capsular contracture (CC) is a frequent and distressing complication of breast augmentation and reconstruction. Although numerous patient-, surgical-, and implant-related risk factors have been proposed, reliable population-level predictors remain inconsistent across studies. This study evaluates whether administrative medical history, as encoded by ICD and CPT codes, contains sufficient predictive signal to identify patients at risk for CC using machine learning. Methods: Patients were queried from the MerativeTM MarketScan® Research Databases from 2003 to 2017 with CPT codes for implant-based breast reconstruction and augmentation. ICD codes were then used to identify all events and conditions of a patient’s history. Hyperparameter-tuned …

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Backscattering By Particles Of Sizes <0.2 Μm In Seawater, Xiaodong Zhang, Yuanheng Xiong May 2026

Backscattering By Particles Of Sizes <0.2 Μm In Seawater, Xiaodong Zhang, Yuanheng Xiong

Faculty Publications

We measured the angular scattering functions at 517 nm in different size fractions, including bulk and very small particles (VSP for diameters <0.2 μm), in a variety of waters ranging from coasts to open oceans and from surface to depths as deep as 3,000 m. The measurements revealed a strong covariation in backscattering between VSP and bulk particle populations. The fractional contribution by VSP decreases from 60% in clear oceanic water where bulk particle backscattering coefficient bbp is on the order of 0.001 m−1 to <2% in turbid coastal water where bbp ∼0.1 m−1. An empirical model is developed (r2 = 0.89) to estimate bbp for VSP from the bulk bbp, which can now be routinely obtained from satellite observations.

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Panda-Plus-Bench: A Clinical Benchmark For Evaluating The Robustness Of Ai Foundation Models In Prostate Cancer Diagnosis, Joshua L. Ebbert, Dennis Della Corte May 2026

Panda-Plus-Bench: A Clinical Benchmark For Evaluating The Robustness Of Ai Foundation Models In Prostate Cancer Diagnosis, Joshua L. Ebbert, Dennis Della Corte

Faculty Publications

Artificial intelligence foundation models are increasingly deployed for prostate cancer Gleason grading, where GP3/GP4 distinction directly impacts treatment decisions (active surveillance vs. intervention). However, these models may achieve high validation accuracy by learning specimen-specific artifacts rather than generalizable biological features, limiting real-world clinical utility. We introduce PANDA-PLUS-Bench, a curated benchmark dataset derived from expertly annotated prostate biopsies designed specifically to quantify this failure mode. The benchmark comprises nine carefully selected whole slide images from nine unique patients containing diverse Gleason patterns, with non-overlapping tissue patches extracted at both 512 × 512 and 224 × 224-pixel resolutions across eight augmentation conditions. …

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Operational Responsibility In Ai Governance: A User-Centric Liability Framework, Zhengyang Chen May 2026

Operational Responsibility In Ai Governance: A User-Centric Liability Framework, Zhengyang Chen

Faculty Publications

Who bears responsibility when artificial intelligence systems cause harm? This question has become central to AI ethics and governance. Most existing approaches focus on developers, yet this faces serious practical and theoretical problems. Drawing on tort law, agency law, and philosophy of technology, this paper argues that AI should be understood as an instrument whose outputs remain the responsibility of human operators rather than developers. We call this 'user-centric governance.' Placing accountability with deployers promotes public trust by creating clear lines of responsibility, a concern that governance approaches have often overlooked. It preserves democratic accountability by keeping human actors answerable …

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Inconsistencies Emerge Between Regional And Local-Scale Water Security Metrics At Military Installations, Abigail Birnbaum, Michael L. Berg, Caitlin Grady, Daniel Weeks, Christopher M. Chini May 2026

Inconsistencies Emerge Between Regional And Local-Scale Water Security Metrics At Military Installations, Abigail Birnbaum, Michael L. Berg, Caitlin Grady, Daniel Weeks, Christopher M. Chini

Faculty Publications

Recent United States federal policy for military installations has emphasized the importance of developing a standardized approach for water security assessment to monitor changes in water resources and the ability for an installation to meet both its civilian and mission needs. For military installations in the United States, these assessments must consider demands both inside and outside the installation’s fence line, as regional resources are required to meet mission readiness. Focusing on physical water scarcity, this study compares four water security metrics with unique formulations and spatial resolutions, including an installation-scale metric and multiple regional metrics defined for either baseline …

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Ai Need Not Make One Slothful, Roy A. Kaelin Jr May 2026

Ai Need Not Make One Slothful, Roy A. Kaelin Jr

Faculty Publications

As National Louis University seeks to plan and advance its way amid the potential perils and pitfalls of so-named artificial intelligence, one finds that with reasonable workflows and guard rails, the use of AI proposes both potential promise and prospect, to assist and augment the natural intelligence that students and teachers bring to the classroom, encouraging them to pursue STEM-related activities with the preparation and deployment of focused and directed AI-bots. This paper presents examples and a case study of that directed and focused approach, the incremental lessons learned to date, and a proposed path to advance worthwhile AI …

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Measurements And Scaling Of Ion Propulsion Impulse During Driven Magnetic Reconnection, Fatima Ebrahimi, Nicholas A. O'Gorman, Kush Maheshwari, Jongsoo Yoo, Alexandre Sainterme, Hantao Ji May 2026

Measurements And Scaling Of Ion Propulsion Impulse During Driven Magnetic Reconnection, Fatima Ebrahimi, Nicholas A. O'Gorman, Kush Maheshwari, Jongsoo Yoo, Alexandre Sainterme, Hantao Ji

Faculty Publications

Impulse scaling during magnetic reconnection, the magnetic energy conversion to kinetic energy, via direct Mach probe measurements in Magnetic Reconnection Experiment is examined. Ion exhaust velocity and impulse scalings with reconnecting magnetic field during the push phase of driven reconnection are presented. The outflows and impulse measurements are compared with global MHD simulations. Both measurements and simulations reveal a favorable scaling, greater than linear, of impulse with reconnecting field. These scaling results establish that magnetic reconnection could be utilized for plasma propulsion.

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Sheets Of Spectral Data Of Stokes Waves In Weakly Nonlinear Models, Benjamin F. Akers, Ryan Creedon Apr 2026

Sheets Of Spectral Data Of Stokes Waves In Weakly Nonlinear Models, Benjamin F. Akers, Ryan Creedon

Faculty Publications

We study the spectral stability of small-amplitude Stokes waves in a family of weakly nonlinear, unidirectional models of the form ut + Lu + (u2)x = 0. We introduce a perturbation method to expand the spectral data in wave amplitude near flat-state eigenvalue collisions, with the ratio of the colliding modes as a free parameter. This yields sheets of spectral data whose slices at fixed amplitude give isolas of instability. The same perturbation framework treats both high-frequency and Benjamin--Feir instabilities, extends to discontinuous dispersion relations (including the Akers--Milewski equation), and, for the first time, provides an …

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