Digital Commons Network^™

The Living Archive: Photography, Social Media, And The New Frontier Of Activism, Lundyn C. Herring

LSU Master's Theses

This thesis seeks to analyze the discursive field and technology of photography and its multi-faceted role in the oppression of colonized people under Western imperialism. Among the main collection highlights of many established state-run archival institutions are photographic records consisting of surveillance images, mugshots, and other visual media as representations of the political hegemony that is exerted over governed peoples. From the mid-19th century to 2026, much has shifted in the realm of photography with the introduction of smartphones, accessible technology, and social media platforms during the beginning of the twenty-first century. As states and powerholders apply the technology of …

Chemical Design Strategies For Hybrid Metal Halide Semiconductors With Enhanced Stability And Optoelectronic Properties, Ali Azmy

USF Tampa Graduate Theses and Dissertations

Metal halide semiconductors have rejuvenated the attention of the scientific community for the last two decades owing to their photophysical and electronic properties. However, these materials have some limitations that hinder their commercialization and widespread application. One major limitation of these materials is their instability under ambient and operating conditions of moisture, head, light and radiation exposure. Here, we report multiple chemical design strategies to address the stability issues of these materials while simultaneously maintaining their exceptional optoelectronic properties. Such design strategies allowed the acquisition of the first members of the family of porous metal halide semiconductors which exhibit record …

Riemann-Hilbert Problems For A Class Of Planar Orthogonal Polynomials, Abril Arenas

USF Tampa Graduate Theses and Dissertations

Planar orthogonal polynomials of degree n are monic polynomials defined by the orthogonality relation,

∫cPn(z)Pm(z)e-V(z) dA(z) = hnδn,m.

where the integration is over the whole complex plane with Lebesgue area measure dA, and hn is a positive norming constant. In this thesis we consider the potential V: CR of the type,

V(z) = |z|2p-2Re Σm j=1 tjzj

we characterize the planar orthogonal polynomials using novel matrix Riemann-Hilbert problems. We pro-pose a Riemann-Hilbert problem of size 2px 2p when the maximal degree satisfies m ≤ p. For m = 2p, we propose a Riemann-Hilbert problem of size 3px 3p for the …

Analyzing The Utilisation Of Chatgpt For Academic Purpose: Exploring Student Motivations, Dr. Sankar P, Nandakumar K

Library Philosophy and Practice (e-journal)

While praising ChatGPT for its ability to produce complex and human-like text, it was hailed as the best AI chatbot ever released to the public. It was also noted that the output was on par with what a competent student could do, suggesting that teachers would have significant challenges down the road. The purpose of this study was to investigate what drives students to use ChatGPT for schoolwork. This study used a descriptive research approach to describe the opinions of Arts and Science College students in the Coimbatore District. The study used a questionnaire to get data from the students' …

Effective Spectrum-Based Antibiotic Resistance Index For Monitoring Resistance In Gram-Negative Bacilli, M Cristina Vazquez Guillamet, Alice Bewley, Nicole J Tarlton, Reid Goodman, Michael J Durkin, Michael Bernauer, Meghan Brett, Kevin Hsueh, Cristian Bologa, George Turabelidze, Andrew Atkinson, Victoria J Fraser

2020-Current year OA Pubs

BACKGROUND: Antimicrobial resistance (AMR) is a growing public health threat, and we currently lack accurate measures to track and trend this resistance. We developed the antibiotic resistance index (ARI) that aggregates resistance of Gram-negative bacilli (GNB) into a single metric which can be tracked across healthcare settings and over time.

METHODS: Culture data were collected from adult patients who met the CDC adult sepsis event criteria across 10 Barnes-Jewish HealthCare (BJC) hospitals between January 2018 and December 2023. An antibiotic's effective spectrum (AES) was calculated as the ratio of susceptible GNB to all identified GNB. The ARI was calculated as …

Post-Silicon Performance Prediction, N/A

Defensive Publications Series

The present disclosure is directed to generating architecture-aware voltage-frequency (VF) scaling curves for semiconductor designs utilizing logic depth normalization to predict post-silicon performance across diverse process, voltage, and temperature (PVT) corners. An approach involves ingesting raw library characterization data for representative standard cells and converting target frequencies into a normalized metric based on cell-specific propagation delays. By iterating through multiple critical path compositions, the approach can identify a worst-case stage depth that represents the architectural speed limit of the design across all corners. This limiting constraint is then mapped back to the raw delay data across a full voltage spectrum …

Slender And Nonslender Delta Wing Simulation And Analysis, Aashish Gyawali, Brinda Bhattarai, Nishesh Bista, Sundeep Rao Dr

Journal of Aviation Technology and Engineering

Stability, controllability, and maneuverability are critical factors for aircraft with short takeoff and landing distances, such as modern fighter aircraft and unmanned aerial vehicles. Delta wings are commonly employed in these aircraft due to their efficient aerodynamics, enabling high maneuverability, and performance at both low and high speeds. Nonslender wings are used for low-speed performance and agility, while slender wings offer reduced drag and are suited for high-speed operations. In flight, an aircraft encounters different airflow patterns including vortices that circulate from the higher-pressure lower side of the wing to the lower-pressure upper side, contributing to lift generation. However, as …

From The Editors..., Thomastine Sarchet-Maher

Journal of Science Education for Students with Disabilities

No abstract provided.

Call For Manuscripts, Thomastine Sarchet-Maher

Journal of Science Education for Students with Disabilities

The Journal of Science Education for Students with Disabilities is a peer-reviewed, open access, multi-disciplinary online journal with an international focus. We publish articles that reflect the best of research and practice related to inclusive science education, including works submitted by science and special education researchers, teacher educators, and teachers. Interesting topics have included innovative curricular ideas, instructional adaptations, research-based modifications, best practices, and management strategies in science education. JSESD adopts the philosophical perspective that all students can achieve in science, and that science benefits from the full participation of all students.

Aperiodic Geometric Stabilization Of Bi-Ionic Plasma Flows, Daniel Schramm

Defensive Publications Series

This disclosure specifies a method for preventing magnetic "pinch factor" instabilities and thermal collapse in high-energy plasma confinement and propulsion systems. Unlike traditional systems that rely on active computer-controlled feedback loops to manage resonance, this framework utilizes the Golden Ratio (approximately 1.618) as a structural constant within the rotational velocity vectors of the plasma. By ensuring a non-repeating rotational ratio between ionic streams, the system mathematically forbids periodic harmonic resonance, creating a self-stabilizing Quasicrystal Magnetic Lattice. This allows for the recycling of waste energy into the stabilization field, ensuring a high-efficiency, win-win energy loop.

2. KEYWORDS

Quasicrystal Magnetic Lattice; Golden …

2025-2026 - Tennessee Winter Climate Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Seasonal and Annual Climate Summaries

No abstract provided.

2026 March 26 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Interview With Orca Award Winner David Hage, Unl Chemistry; Drug-Protein Interactions, Mark Griep, David Hage

UNL ORCA Interview Series

Prof. David Hage was awarded the ORCA in 2018. He was born in La Crosse, Wisconsin, and earned a bachelor’s in chemistry at the University of Wisconsin in La Crosse. Next, he earned a doctorate from Iowa State University and did postdoctoral work at the Mayo Clinic in Rochester, Minnesota. In 1989, he joined UNL as an assistant professor of chemistry and quickly rose through the ranks. He has won many awards and, for the past 13 years, has been the James Hewet University Professor of Chemistry. Allow me to share some remarkable facts about Dave before we get into …

The Waldo Dataset, Mary E. Koone, Rosie Kallie, Vassilis Athisos, Laurel S. Stvan

Computer Science and Engineering Datasets - Archive

Distinct from the task of predicting the author of a document (authorship attribution), we focus on addressing the issue of how to estimate the similarity between the written language styles of authors. To do so, we present a dataset of metadata derived by asking human annotators, who were presented with three documents, to identify which two were written by the same author and which was written by a different author. The dataset has over 400 such annotations, creating a companion to the Amazon Web Services (AWS) customer review dataset, laying the groundwork for crowdsourcing applications to other natural language processing …

Minimax Lower Bounds For Uniform Estimation Of Covariate-Dependent Copula Parameters, Mathias Muia

Probability & Statistics Seminar

In this talk, we analyze uniform estimation of covariate-dependent copula parameters using local likelihood methods. Building on our recent preprint establishing uniform stochastic equicontinuity and convergence rates, we derive minimax lower bounds over Holder classes of calibration functions. Under mild regularity conditions on the copula family and the covariate design, we show that the minimax sup-norm risk over a compact covariate region is bounded below by the classical nonparametric rate for smooth functions on an s-dimensional domain. The proof combines a localized packing construction with a Fano–Le Cam testing argument, using second-order expansions of the conditional copula likelihood to control …

The Α-Test: A New Statistical Test For The Selection Of Reliable Principal Components, Seongjai Kim

Probability & Statistics Seminar

Principal component analysis (PCA) is a statistical technique for the dimensionality reduction of data, minimizing information loss and increasing interpretability. It does so by first extracting new uncorrelated variables which successively maximize variance in the remaining data spaces and then cutting off principal components (PCs) corresponding to small singular values.

However, for various applications, certain PCs must be eliminated to enhance the stability and reliability, although the corresponding singular values are not small. This article introduces an innovative statistical criterion for the selection of reliable PCs, called the α-Test.

The proposed test is analyzed, and effective computational algorithms are discussed …

Role Of Wadsley Defects And Cation Disorder To Enhance Monb12O33 Diffusion, Cj Sturgill, Manish Kumar, Nima Karimitari, Iva Millisavljevic, Coby S. Collins, Aaron Hegler, Hsin-Yun Joy Chao, Santosh Kiran Balijepalli, Scott T. Misture, Christopher Sutton, Morgan Stefik

Faculty Publications

Wadsley-Roth (WR) niobates have emerged as high-rate anode materials that can combine rapid ionic diffusion with good electronic conductivity. WR compounds have been defect-enhanced by limited annealing, however, such materials often contain multiple types of defects. In particular, both Wadsley defects (variable block size) and transition metal disorder have the potential to modify transport rates, however the corresponding effects are not well understood mechanistically. Here, MoNb12O33 (MNO) was calcined at two different temperatures to compare a defect-rich condition (MNO-800) with a proximal order-rich condition (MNO-900) as assessed through XRD, XANES, EXAFS, and STEM characterizations. Galvanostatically cycled lithium half cells of …

A Comprehensive Survey Of Watermarking Techniques For Copyright Protection And Integrity Verification On Dnns And Generative Models, Xinyun Liu, Ronghua Xu

Michigan Tech Publications

Deep neural networks (DNNs) have made remarkable progress in recent years and are widely applied across many fields. Trained DNNs are valuable assets due to their dependence on large volumes of quality data, expensive computational resources, and the development of sophisticated architectures. However, their increasing vulnerability to intellectual property (IP) infringement, including unauthorized use, replication, and redistribution, underscores the critical need for adequate copyright protection and integrity verification. DNN model watermarking has emerged as a promising solution to these challenges by embedding imperceptible identifiers into models. This survey provides a concise yet comprehensive state-of-the-art review of watermarking techniques focusing on …

Pdxscholar Annual Report 2025, Julia Stone, Bertrand Robinson, Stacey Schlatter, Carolee Harrison

Library Faculty and Staff Publications and Presentations

This PDXScholar Annual Report covers the period between January 1, 2025, and December 31, 2025. This report demonstrates PDXScholar’s continued impact through readership data, new and growing collections, and comments and feedback from our users.

Effect Of Light Elements On The Melting Behavior Of Liquid Iron Alloys Under Earth’S Inner Core Boundary Conditions, Olaniyi Anisere

LSU Master's Theses

The temperature at Earth’s inner core boundary (ICB) is set by the melting temperature of the iron-rich outer core at core pressures, yet this remains uncertain because melting depends strongly on composition and pressure. Light elements are required to explain the core’s density deficit, but the identity, abundance, and combined influence of these elements on melting under ICB conditions are still debated. This thesis quantifies how candidate light elements modify the melting behavior of iron alloys at ICB-relevant pressures and uses these composition-dependent melting relations to constrain ICB temperature.

Melting relations were determined using molecular dynamics simulations in VASP accelerated …

A Comprehensive Survey Of Watermarking Techniques For Copyright Protection And Integrity Verification On Dnns And Generative Models, Xinyun Liu, Ronghua Xu

Michigan Tech Publications

Deep neural networks (DNNs) have made remarkable progress in recent years and are widely applied across many fields. Trained DNNs are valuable assets due to their dependence on large volumes of quality data, expensive computational resources, and the development of sophisticated architectures. However, their increasing vulnerability to intellectual property (IP) infringement, including unauthorized use, replication, and redistribution, underscores the critical need for adequate copyright protection and integrity verification. DNN model watermarking has emerged as a promising solution to these challenges by embedding imperceptible identifiers into models. This survey provides a concise yet comprehensive state-of-the-art review of watermarking techniques focusing on …

Objective Conditioning Via Latent-Factor Modeling, Kalman-Smoothing, And Hidden Markov Clustering: An Application To Empirical Asset Pricing, Melanie R. Neller

Theses and Dissertations

Empirical asset pricing relies heavily on conditioning sets--industry groupings, size buckets, valuation screens, and other researcher-defined partitions--to structure cross-sectional tests and portfolio construction. While intuitive, such partitions risk blending heterogeneous firms, masking latent exposures, and introducing omitted-variable bias. This thesis develops an objective, mathematically grounded conditioning pipeline that replaces subjective groupings with latent-factor extraction, Kalman-based data techniques, and probabilistic clustering via Gaussian hidden Markov models (HMMs). Using CRSP monthly returns, the framework stabilizes noisy return data, extracts systematic structure through principal component analysis (PCA), identifies homogeneous stock cohorts through HMM clustering, and models regime persistence using Markov transition matrices. These …

Curriculum For A Two Semester Calculus Course Specializing In Life Science And Data Science, Patrick Mcclain

LSU Master's Theses

Traditionally, introductory calculus has been designed for engineering and physics students, often leaving students majoring in data science or life sciences with a curriculum that lacks professional relevance and is overly reliant on problems that focus on computational fluency. This thesis proposes a two-semester sequence, called MATH 153X and MATH 154X, specifically tailored for the Louisiana State University (LSU) Dual Enrollment program and university-level data science and life sciences majors. By integrating modern computational tools—such as symbolic calculators and artificial intelligence (AI) tools—the proposed curriculum shifts the pedagogical focus from procedural symbolic manipulation toward conceptual literacy.

Through a series …

Deep Learning Based Control System For Multi-Zone Hvac Residential Buildings, Mohammad H. Z. Alghalayeeni

Mechanical Engineering Theses

Heating, ventilation, and air conditioning (HVAC) systems are major contributors to residential energy consumption. However, most homes continue to rely on single zone thermostat control, which regulates temperature based on a single sensor and cannot account for thermal variations across multiple rooms. This often leads to uneven thermal conditions and inefficient energy use in multi-zone residential buildings. This thesis presents a deep reinforcement learning based approach for improving HVAC zoning control through dynamic airflow distribution. A physics based multi zone thermal model of a residential house was developed to simulate heat transfer processes including conduction, convection, solar and internal heat …

Rethinking How The United States And Mexico Share The Colorado River, Eric Kuhn, Anne Castle, Carlos De La Parra, John Fleck, Jack Schmidt, Kathryn Sorensen, Katherine Tara

The Traveling Wilburys of the Colorado River

Since 1945, the United States and Mexico have managed common interests on their two largest shared rivers systems, the Colorado and the Rio Bravo/Rio Grande, under the terms of the 1944 international treaty that was designed from the beginning with tools to adapt to changing hydrologic and societal conditions. A recent emergency agreement on the Rio Bravo/Rio Grande illustrates what is possible, and with old river management rules on the Colorado both within the United States and between the United States and Mexico about to expire, we are at a moment of opportunity for meaningful change. The core problem on …

Towards Understanding Robust Neural Coding Through Representational Geometry, Zeyuan Ye

Arts & Sciences Graduate Student Theses and Dissertations

Neural activity is high-dimensional and variable, yet animals represent information robustly. This thesis studies the origins of such robustness through the lens of representational geometry and deep neural network modeling. From a geometric perspective, population responses concentrate near smooth manifolds embedded in a high-dimensional state space. To infer these manifolds from noisy data and quantify their geometric properties, we develop a statistical method based on Gaussian processes and kernel regression (GKR). Applying GKR to simultaneously recorded grid-cell population activity during open-field navigation, we show that increasing running speed expands a torus-like representational manifold and improves spatial decodability. Thus, despite faster …

March 26, 2026, The Daily Mississippian

Daily Mississippian (all digitized issues)

No abstract provided.

March 26, 2026, James Madison University

The Breeze, 2020-

The Breeze is the student newspaper of James Madison University in Harrisonburg, Virginia.

Properties Of The Graph Modularity Matrix And Its Applications, Benjamin Quiring, Panayot S. Vassilevski

Mathematics and Statistics Faculty Publications and Presentations

We study the popular modularity matrix and respective functional ([20]) used in connection with graph clustering and derive some properties useful when performing vertex aggregation of the associated graph. These properties are employed in the derivation of a multilevel parallel pairwise aggregation algorithm. Comparative performance results of the studied algorithm applied to graph clustering tested against the popular Louvain algorithm [4], [3] are presented. Some illustrative examples show that the resulting aggregates if used in an adaptive algebraic multigrid (AMG) are able to follow strong direction of anisotropy in finite element problems. 1.

Making The Right Decisions For Adaptive Radiotherapy, Chloe C.F. Ditusa

LSU Doctoral Dissertations

Purpose: Daily anatomical changes can invalidate the geometric, dosimetric, and biological assumptions of reference radiotherapy plans, yet quantitative evidence describing fraction-level deviations across disease sites remains limited. This work developed and evaluated a metric-based framework for daily dose assessment to characterize temporal treatment behavior and inform adaptive decision-making in Head and Neck (H&N) radiotherapy and Prostate stereotactic body radiotherapy (SBRT). Methods: A web-based Dashboard was created to compute geometric, dosimetric, and radiobiological metrics from daily dose recalculations. Calculations were first verified against a commercial treatment-planning analysis platform. Daily dose on anatomy-of-the-day was reconstructed using CBCT-based pseudo-CTs for H&N and daily …