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Ammonium Phosphate Fertilizers Are A More Effective Phosphorus Source Than Superphosphate For Wheat Grown On Acidic Gravelly Soils, Craig A. Scanlan, Raj Malik, Fien Degryse, Andrew Van Burgel, Mike J. Mclaughlin

Grain and Other Field Crops Research Articles

Selecting the most effective phosphorus (P) fertilizer source is essential for maximizing crop yields. However, there is little information to guide the choice between the widely used soluble granular sources: ammonium phosphates and superphosphates. The aims of this study were to examine whether there are differences in wheat (Triticum aestivum L.) grain yield response to ammonium phosphate and superphosphate fertilizers in field conditions, and if these differences relate to diffusion of P from fertilizer granules. Two field experiments were conducted on acidic gravelly soils in Western Australia where P deficiency occurs to compare wheat growth response to P applied …

Properties Of Enjoyable Mathematical Contexts From The Student Perspective, Emilie Nadine Hendrickson

Theses and Dissertations

Researchers continue to grapple with how to meaningfully engage students in mathematical content. Many students report disengagement due to perceptions that mathematics is difficult, irrelevant, boring, or anxiety-inducing. This study sought to understand how students interpret and respond to different mathematical problem contexts, with particular attention to the reasons students describe certain problems as enjoyable or unenjoyable. Using semi-structured interviews, this research examined student responses to a variety of mathematical problem types primarily across affective engagement. Students reflected on specific problem contexts and explained which features supported or hindered their enjoyment and engagement. Students described that contexts were enjoyable have …

Clinical Utility Of An Fda-Authorized Artificial Intelligence Imaging Platform In Interstitial Lung Disease Diagnosis, Arjun Prakash Tambe, Ryan Boente, Gautam George, Fayez Kheir, Omid Tahamtani Omran, Kavitha Selvan

Division of Pulmonary, Allergy, and Critical Care Medicine Faculty Papers

Background/Objectives: The diagnosis of interstitial lung disease (ILD) is challenging and frequently delayed. Clinically accessible and minimally invasive diagnostic tools are needed to expedite the diagnosis of ILD while minimizing risk to patients. Fibresolve is an imaging artificial intelligence (AI) tool recently approved by the Food and Drug Administration (FDA) for use in ILD diagnosis and made available to clinicians. The objective of this study was to describe its utility in clinical practice. Methods: We conducted a prospective, observational study of patients across the United States (US) in whom Fibresolve was utilized during routine clinical practice between July 2024 and …

Dynamind: A Dynamic Learned Index For Update-Intensive Workloads, Jingxian Cheng, Yingfang Wang, Tianqing Zhu, Xu Yang, Ningning Cui, Jianxin Li

Research outputs 2022 to 2026

Learned indexes leverage machine learning models to approximate data distributions and predict key positions, offering better performance than traditional index structures such as B+Trees. As data in real-world applications evolve rapidly, the timely and efficient updating of learned indexes has become an increasingly important research problem, attracting growing attention in recent studies. However, under update-intensive workloads with frequent insertions and deletions, existing learned indexes cannot update the model in a timely manner. Moreover, they ignore the impact of deletions on model accuracy. These limitations lead to degraded prediction accuracy and increased query latency, undermining the core advantage of learned indexes. …

Ai And The Music Industry: Its Current Status And A Speculative Projection Of Its Evolutionary Trajectory, Rhett D. Morris, Clayton Rosati, Stefan Fritsch

Honors Projects

Music serves as one of society's biggest cultural outlets, allowing millions to share in what used to be a uniquely human form of expression. The commodification of music has built a huge industry full of companies and platforms that have used technology and property laws to shape music's relationship with the public. This study aims to look into the future to see how AI and its implementation could affect the structure of the music industry. To look into the future, this piece establishes two of the most pressing kinds of AI technology for the music industry and looks to contextualize …

Toroidal Plasmonic Nanodimers For Enhanced Near-Infrared Emission In Heterostructured Inp Quantum Dots, Arda Gülücü, Emre Ozan Polat

Turkish Journal of Physics

Near-infrared (NIR) emitters operating in the 650--900 nm spectral range are highly attractive for imaging and sensing in turbid media. However, cadmium-free InP-based quantum dots (QDs) often exhibit limited brightness owing to nonradiative recombination pathways and inefficient photon outcoupling. In particular, heterostructured InP QDs may possess band alignments that induce partial spatial separation of charge carriers, thereby reducing the electron-hole wavefunction overlap. This characteristic modifies the intrinsic recombination dynamics and increases the sensitivity of their emission to the surrounding photonic environment. Here, we investigate silver toroidal plasmonic nanoantenna dimers (Ag TPNDs) using finite-difference time-domain (FDTD) simulations as a geometry-tunable platform …

Influence Of Transboundary Wildfire Smoke On Fine Particulate Matter Concentrations At South Texas Border Schools, Sai Deepak Pinakana, Kabir Bahadur Shah, Owen Temby, Dawid K. Wladyka, Juan L. Gonzalez, Md Saydur Rahman, Katarzyna Sepielak, Amit U. Raysoni

School of Earth, Environmental, & Marine Sciences Faculty Publications

Exposure to air pollutants in indoor and outdoor school environments poses significant health risks to children due to their heightened vulnerability. Increasing wildfire frequency has intensified transboundary smoke transport, with border communities among the first to experience associated air quality impacts. While the impacts of wildfires on air quality are increasingly recognized through satellite observations and modeling, ground-based observations remain scarce in under-monitored regions. Low-cost air sensors were deployed across schools in the Roma and Rio Grande City areas of Starr County, along the U.S.–Mexico border, for 146-days from November 2023 to April 2024. The raw sensor measurements were corrected …

A Semantic Data Management Framework For Uncertainty Quantification In Synchrotron Diffraction Pattern Analysis, Ayorinde E. Olatunde, Ozan Dernek, Erika I. Barcelos, Roger H. French, Anirban Mondal

Student Scholarship

Advancements in technology have enabled scientists and engineers in the synchrotron science domain to generate high-dimensional data. To conduct a machine learning study on these data, an analyst undergoes multiple analytical stages, including dimensionality reduction, predictive modelling, and uncertainty quantification (UQ).

To ensure reproducibility in science, it is necessary to document the semantic relationships among the stages of the analysis to enable provenance, interoperability, and knowledge reuse. In this work, we present a Semantic Data Management (SDM) framework rooted in FAIR principles that provides ontologies for UQ workflows. We illustrate the application of UQ ontology in synchrotron diffraction pattern analyses …

Extreme Heat And Its Impact On Public Transit Ridership In Nyc, Craig Denton

Theses and Dissertations

This thesis explores the connection between extreme heat events and public transit ridership patterns in New York City, with a particular emphasis on low-income communities. It investigates the intersection of socioeconomic factors and heat-related challenges, analyzing how extreme temperature periods influence overall transit use and why certain routes or neighborhoods experience greater declines in ridership during these events.

Utilizing existing literature, NYC-specific transit and climate datasets, and the broader context of transit equity, this research aims to inform strategies that strengthen climate resilience within urban transportation systems. The study’s findings are intended to support policy development and planning initiatives that …

On A Classification Of Goy/Sabra-Type Shell Models Of Turbulence, Austin Ho

Theses and Dissertations

Since their inception in the 1970s, shell models have proved to be a fruitful testbed for studying theories of turbulence. This thesis considers variations of two classical shell models: the Gledzer–Ohkitani–Yamada (GOY) model and the Sabra model. Up to conjugacy classes, we classify all possible GOY-type and Sabra-type models. We numerically approximate the scaling exponents for the newly identified models and develop their mathematical well-posedness.

Revised Draft Final Butte Mine Waste Repository Operation And Maintenance (O&M) Plan, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final Bpsou Unreclaimed Sites: Ur-46 Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Changes In Water Quality And Microbiota Over Two Years In Florida Hard Clam (Mercenaria Mercenaria) Hatcheries, Bonnie Getter

Electronic Theses and Dissertations 2020 - Present

This thesis characterized the water quality and bacterial communities in nine hard clam hatcheries over two production years through weekly or biweekly water quality and chemistry monitoring, monthly bacterial plating in the second year of production, and select 16S microbiome sampling at select hatcheries to address production bottlenecks and support the reliable production of high-quality seed for Florida’s growing hard clam aquaculture industry. Logistic regression models showed that water source was distinguished by pH, salinity, alkalinity, and nitrite, whereas geographic location was distinguished by temperature, salinity, nitrate, and calcium; temperature, dissolved oxygen, salinity, and alkalinity distinguished seasons. Vibrio bacteria differed …

The Effect Of Spin Polarization On Ion-Acoustic Solitary Waves In Quantum Plasmas, Amirhosein Rezvani, Sedigheh Miraboutalebi, Leila Rajaei, Mahmoodreza Sharifian

Turkish Journal of Physics

The exchange interaction, a fundamentally quantum-mechanical phenomenon, can significantly modify the classical description of cold, overdense plasmas. These quantum effects can be systematically analyzed within the framework of quantum magnetohydrodynamic (QMHD) theory, which enables the use of separate momentum equations for spin-up and spin-down electron populations. In this study, we adopt this approach to incorporate exchange interactions for both spin species and investigate the excitation of ion-acoustic wave (IAW) solitons in the plasma system. Using a perturbative expansion method, the governing equations are reduced to a nonlinear Schrödinger equation (NLSE), which admits solitonic wave solutions. The stability of these solitons …

Radiation Pressure And Membrane Dynamics In Cavity Optomechanics: Interaction Hamiltonian And Quantization, Mahmut Can Özuygur

Turkish Journal of Physics

Cavity optomechanics explores the interaction between light confined in optical cavities and mechanical oscillators, primarily driven by radiation pressure forces. These interactions enable significant advances in precision measurements, quantum information processing, and tests of fundamental quantum mechanics. This paper presents a detailed analysis of membrane vibration and radiation pressure force within a cavity optomechanical system. The membrane's equation of motion is derived, the radiation pressure force is evaluated within the Lorentz force formalism, and the corresponding interaction Hamiltonian is formulated. Quantization of the resulting Hamiltonian enables the investigation of quantum phenomena, including entanglement generation and quantum state transfer, and provides …

Observational Constraints On The Structure-Induced Dark Energy Model, Ali̇ Kazim Çamlibel

Turkish Journal of Physics

A new phenomenological dark energy model, originally associated with large-scale structure formation and proposed as a solution to the fine-tuning and coincidence problems related to the cosmological constant, was analyzed within the framework of General Relativity in a Friedmann-Robertson-Walker spacetime and its model parameters were estimated using cosmic chronometers and recent DESI data. It turns out that the proposed model can serve as an alternative evolving dark energy model with a novel equation of state function. Given the form of this phenomenological energy density ansatz, which rises with the nonlinear structure growth in the universe and declines as cosmic voids …

On Cosmological Equation Of State From The First Law Of Thermodynamics, Ch'ng Han Siong

Turkish Journal of Physics

We derive several equations of state for different types of energy from the first law of thermodynamics. We derive the equation of state of a Machian universe from the well-known energy formulaE=mc2. This equation of state is consistent with previously reported results. We then propose hypothetical forms of energy that lead to the equations of state of the Chaplygin gas, generalized Chaplygin gas, and modified Chaplygin gas. We also obtain the energy density of the Chaplygin gas by dividing the hypothetical energy by the volume of the universe, and find that it is consistent with previously reported results. Finally, we …

Design And Fabrication Of Petri Dish Optimized For High-Frequency Acoustic Microscopy Using 3d Printing, Tuna Pesen, Beyza Ceren Eren, Arda İnanç, Bora Akgün

Turkish Journal of Physics

High-frequency imaging in acoustic microscopy requires the use of Petri dishes with thin and acoustically transparent bottoms to minimize signal attenuation and distortion. Commercially available options suitable for this purpose are often expensive or limited in compatibility with custom setups. Here, we present a cost-effective and easily customizable alternative developed in our laboratory, consisting of a 3D-printed frame combined with commercially available stretch film. The stretch film serves as an ultrathin (8 µm thickness) base that supports efficient high-frequency acoustic transmission, enabling clear and reliable imaging. Beyond acoustic microscopy, the adaptable design is also compatible with other modalities such as …

From Homogeneous To Heterogeneous Adaptive Bounded-Confidence Opinion Dynamics On Networks, Sally Hafez, Fatma R. Farag, Amira S. N. Tawadros

Northeast Journal of Complex Systems (NEJCS)

Adaptive bounded-confidence models (ABCMs) elucidate the coevolution of agent states and network structure via local interactions and rewiring mechanisms. Traditional formulations assume uniform interaction parameters, leading to distinct regime shifts encompassing fragmentation, polarization, and consensus. A symmetric heterogeneous extension of the adaptive bounded-confidence model is introduced, in which interaction parameters vary according to whether agents belong to the same or different groups. The model retains the original update and rewiring protocols but integrates within-group and between-group confidence bounds alongside tolerance thresholds. Initially, the classic homogeneous model is replicated to establish a reference point. Subsequently, the heterogeneous extension is assessed under …

Wavelet-Based Multiscale Analysis Of Cave Co₂ Concentration In Response To Short-Term High-Intensity Tourism Activities: Spatiotemporal Heterogeneity And Lag Characteristics, Mingda Cao, Wenwen Song, Yan Zhang, Jie Zhang, Zhiqiang Yao

International Journal of Speleology

High-intensity tourism activities can cause a significant increase in cave air CO₂ concentration, thereby affecting the cave micro-environment and secondary carbonate deposition. During the 2023 National Day Golden Week, high-frequency continuous monitoring of cave air CO₂ partial pressure (PCO_2(A)) and visitor numbers was conducted in Dawang Cave, Anhui Province. Wavelet transform and cross-correlation analyses were used to reveal the multi-scale response characteristics of CO₂ concentration to tourism activities. The results show that: (1) PCO_2(A) exhibited clear diurnal variations (higher during the day, lower at night) and decreased spatially with enhanced ventilation, controlled jointly by …

Community Detection In Bipartite Networks Using Bipartite Stochastic Block Models With Node-Level Covariates, Geraldine Elaine Percival

Dissertations

In this age, monumental webs of data demands for perpetual cultivation of ways to untangle these webs of information. One of the many curiosities is how to systematically group entities. When clustering, one avenue to take is ascertaining the interconnectedness between the data points, and gauging their influence to each other. This perspective is programmed to model the relationships between the data presented as a network. Many of the methods being used today are algorithm-based, which may pose limitations in understanding and explaining the uncertainty revolving around the data. Hence, it is proposed to steer towards a model-based approach that …

Improving Tensorsketch Using Complex Random Variables, Amit Sharma, Mohammad Azhar Khan, Rameshwar Pratap, Keegan Kang

Faculty Conference Papers and Presentations

TensorSketch by Pham and Pagh [2013], Kar and Karnick [2012] provides efficient sketching algorithms for highdimensional polynomial kernels $\vec{x}^{\otimes p} \in \R^{d^p}$. Kar and Karnick [2012] uses dense Johnson-Lindenstrauss (JL)-type projections with computational cost $O(pDd)$, whereas Pham and Pagh [2013] extends the sparse CountSketch [Charikar et al., 2024] algorithm, yielding a faster algorithm for high-dimensional sparse inputs with running time $O\left(p(\nnz{\vec{x}} + D \log D)\right)$. However, the variance of both estimators grows exponentially with the polynomial degree $p$, scaling as $3^{p}/D$, where $D$ denotes the sketch dimension. Recent work by Wacker et al. [2023] showed that using complex-valued distribution reduces …

Dbssnet: Dual-Branch Spectral-Spatial Network With Data-Driven And Knowledge-Guided Band Selection For Uav Hyperspectral Wheat Rust Detection, Subin Kim

All Graduate Theses and Dissertations, Fall 2023 to Present

Wheat rust is a serious plant disease that can reduce crop yield and quality. In practice, the disease is often noticed only after visible symptoms appear, when some damage may already be difficult to reverse. This thesis studies whether drone-based imaging can help detect wheat rust earlier and more reliably in field environments. 

Unlike an ordinary color photograph, a hyperspectral image records reflected light at many narrow wavelengths. These measurements can reveal useful information about plant condition, but they are also high dimensional, noisy, and difficult to analyze when only a limited number of labeled field samples are available. To …

Mining Time Series Shapelets And Association Rules For Solar Flare Prediction, Drew Watson

All Graduate Theses and Dissertations, Fall 2023 to Present

Solar flares are the largest explosions in the solar system; they are caused by changes in the Sun’s magnetic field. Strong solar flares can disrupt power systems, damage satellites, and interfere with radio communication, so improving flare prediction is important. This thesis develops a way to predict severe solar flares while also helping researchers understand why those predictions are made. The approach looks for short patterns in solar magnetic field data that are linked to future flare activity. It then studies how these patterns appear together and in what order they happen over time. By doing this, the research not …

Assessing The Health Impacts Of Pm2.5 And Ozone Exposure: A Study Of Hospitalizations In El Paso, Alexia Breanna Reyes

Open Access Theses & Dissertations

Air pollution has been widely associated with adverse cardiovascular health outcomes; however, most research in arid regions has focused on high-intensity dust events rather than routine, non-dust conditions. This study aimed to evaluate the association between non-dust air pollution and cardiovascular hospitalizations in El Paso County, Texas. A time series analysis was conducted using hospitalization data from 2010 to 2014. Daily counts on non-dust event days of cardiovascular hospitalizations, including hypertensive diseases, ischemic heart disease, cerebrovascular disease, and diseases of pulmonary circulation, were examined in relation to ambient concentrations of fine particulate matter (PM2.5) and ozone. Quasi-Poisson regression models with …

Sentinel: Evaluating Occlusion-Centered Next-Best-View Selection Using Rgb-Derived Pseudo-Geometry, Paul Nassar

Master's Theses

Three-dimensional cameras provide direct geometric measurements, but their cost, weight, power requirements, and calibration constraints can limit their use in various lightweight or large-scale sensing systems. A potential alternative is to use conventional two-dimensional RGB cameras together with geometric reconstruction models that infer a partial three-dimensional representation from images. This thesis evaluates that possibility for next-best-view (NBV) selection through Sentinel, an occlusion-centered system for static, object-centric scenes with known camera poses and intrinsics. Sentinel converts source RGB observations into pseudo-geometry using monocular depth or point-map predictions, combines those predictions with camera-ray evidence, identifies occluded unknown regions, and selects a candidate …

Laplace Factor Models In High-Dimensional Data, Siqi Liu, Xuerong Meggie Wen, Akim Adekpedjou, Guangbao Guo

Mathematics and Statistics Faculty Research & Creative Works

Laplace factor models (LFMs) provide a heavy-tailed alternative to Gaussian factor models by representing high-dimensional observations through a low-rank common component and Laplace-distributed idiosyncratic errors. This paper develops an assumption-consistent finite-sample analysis of matrix concentration, covariance estimation, and Monte Carlo integration under this model. We first formulate the model with explicit dimensional, independence, covariance, and identifiability conditions. Standard matrix Laplace-transform and matrix Bernstein inequalities are then recalled with their precise applicability conditions. Because untruncated Laplace variables are neither almost surely bounded nor strongly log-concave, these standard results cannot be applied directly in the forms commonly used for bounded or Gaussian-like …

Enabling Multi-Task Neural Network Inference On Heterogeneous Edge Devices, Redwanul Islam Arif

Master's Theses

Deep neural networks are increasingly required to run on the devices that generate the data. If such a device must perform more than one task, the standard practice is deploying one model per task, which makes memory grow linearly with task count, which is unacceptable when the entire budget is kilobytes. This thesis asks one question in three settings: how much capability can a network acquire without incurring deployment cost?

The first study takes an ImageNet-pretrained ResNet-18, sweeps the branch point across every residual stage and the classification-head depth across one, ten, and twenty layers, and deploys the resulting multi-head …

Federated Learning For Early Medical Diagnosis: Enhanced Diabetic Retinopathy Detection In Smart Healthcare, Mohammad Nasajpour Esfahani

Master's Theses

This thesis investigates the role of federated learning as a privacy-preserving solution for modern healthcare challenges. In traditional machine learning, sensitive medical data must be centralized for model training, raising concerns about privacy, security, and regulatory compliance. Federated learning offers an alternative by allowing hospitals, clinics, and personal health devices to collaboratively train shared models without exchanging raw patient data. The study first explores how federated learning is being used across various healthcare domains, including cancer detection, medical imaging, and disease prediction— highlighting its potential to support secure collaboration across institutions. It addresses key benefits such as data privacy, scalability, …

Mono Gold: An Informal Account Of The Geology, Production, And History Of Mono County Gold And Silver Mining Districts, D. D. Trent

Eastern Sierra History Journal

Mono Gold explores the mining production, technology, and history of the Eastern Sierra, with a special focus on Mono County. Author Dee Trent, a geologist, spent decades visiting, researching, and photographing each of the mining operations discussed in this book-length monograph.