Digital Commons Network^™

Dry After-Ripening Increases Germination Of Critically Imperilled Physaria Thamnophila (Zapata Bladderpod), Christopher A. Gabler, Jerald T. Garrett

School of Earth, Environmental, & Marine Sciences Faculty Publications

Effective endangered plant conservation and recovery require empirical knowledge of seed dormancy release and responses to post-collection handling, yet such information is lacking for many rare taxa. Physaria thamnophila (Zapata bladderpod; Brassicaceae), a critically imperilled (G1) species endemic to southern Texas, USA, is poorly studied, and basic questions regarding seed storage and germination remain unresolved. We evaluated the effects of short-term cool-storage duration (14–180 d), storage temperature (refrigeration vs. freezing), dry after-ripening and maternal plant identity on germination probability and timing in P. thamnophila. Dry after-ripening and increased cool-storage duration consistently increased germination and shortened germination time, whereas storage temperature …

Characterizing Candidate Blazar Counterparts Of The Ultra-High-Energy Event Km3-230213a, O. Adriani, S. Aiello, A. Albert, A. R. Alhebsi, M. Alshamsi, S. Alves Garre, S. Rani, Et Al.

Michigan Tech Publications

High-energy astrophysical neutrinos serve as crucial messengers for understanding hadronic acceleration processes and identifying the origins of cosmic rays, with blazars among the most promising neutrino sources. The KM3NeT experiment reported the detection of an ultrahigh-energy neutrino with an energy estimate of ∼220 PeV, the most energetic yet observed. The neutrino arrival direction has a 99% confidence region of 3° radius centered at R.A. 94 (Formula presented) .° 3, decl. −7 (Formula presented) .° 8 (J2000). In this work, 17 candidate blazars located within this region are identified. Comprehensive new observations and archival data analysis for these sources are presented. …

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 …

Real Bullets, Plastic Guns: Evaluating The Strength Of 3-D Printed Gun Parts, Maria Latenia Mayol

Student Theses

Privately made firearms (PMFs), often referred to as “ghost guns,” are firearms manufactured or assembled by individuals rather than federally licensed manufacturers. Although the terms are frequently used interchangeably, “ghost gun” more specifically describes an unserialized firearm, whereas PMFs include a broader range of firearms produced through nontraditional manufacturing methods. PMFs may be entirely 3-D printed, assembled from partially completed firearm kits, or constructed by integrating additively manufactured components with commercially manufactured firearm parts. The increasing accessibility of additive manufacturing and widespread dissemination of computer-aided design files have raised concerns about concealment, regulation, and forensic evasion, particularly when factory-manufactured components …

A Granularity-Centered Taxonomy Of Personalized Federated Learning, Ei Ei Nyein Chan, Sergei Chuprov, Pretom Roy Ovi, Kamrul Hasan

Computer Science Faculty Publications

Personalized Federated Learning (PFL) has emerged as a key approach to address performance degradation in FL systems under heterogeneous client data. While existing surveys typically categorize PFL methods based on optimization strategies or system-level mechanisms, they often overlook a fundamental question: where is personalization embedded within the model architecture? In this survey, we bridge this knowledge gap and introduce a granularity-centered taxonomy that organizes PFL approaches according to the structural depth of personalization, ranging from head-layer and layer-wise adaptation to model-wise and parameter-wise customization. This novel perspective helps practitioners select appropriate personalization strategies based on model architecture, data heterogeneity, and …

From Reluctance To Resilience: The Link Between Attitude And Growth Mindset In Calculus Students, Olivia Valente, Kathryn E. Pedings-Behling, Amy N. Langville

Journal of Educational Research and Practice

Many postsecondary students enter general education mathematics courses with negative attitudes, shaping their willingness to engage with the content. This study explores the relationship between students’ attitudes towards mathematics and their growth mindset, revealing effective strategies to enhance learning experiences, particularly for students who are reluctant learners. The research investigates two questions: (1) How do students’ Attitude Toward Mathematics Inventory (ATMI) scores and Growth Mindset Scale (GMS) scores relate? and (2) Do gender or course modality affect this relationship? This study addresses a gap in literature by examining how enjoyment, motivation, self-confidence, and perceived value connect with growth mindset. The …

Measuring Cosmic Expansion From Early To Late Times Using Quasars, Galaxies, & Local Supernovae, Rajeev Vaisakh

Physics Theses and Dissertations

This dissertation investigates the evolution of cosmic expansion across a wide redshift ($z$) range by combining measurements from quasars \& galaxies in the distant universe $(z > 0.8)$ with those obtained from stripped-core collapse supernovae observations from the nearby universe $(z < 0.1)$. Using the DESI spectroscopic survey, we analyze large-scale clustering from quasars over $0.8 < z < 2.1$ and emission line galaxies over $0.8 < z < 1.6$, contributing to DESI DR2 BAO and full-shape measurements of cosmic expansion and structure growth. Combined with BBN in flat $\Lambda$CDM, DESI DR2 BAO gives $H_0 = 68.51 \pm 0.58$ km s$^{-1}$ Mpc$^{-1}$, while combinations of DESI BAO with CMB and supernova data show a preference for evolving dark energy, with representative constraints such as $w_0 = -0.752 \pm 0.057$ and $w_a = -0.86^{+0.23}_{-0.20}$ for DESI+CMB+DESY5. Using the ROTSE-III Supernova Survey and the expanding photosphere method (EPM), we measure distances to a sample of six supernovae for which the thermal phase can be clearly identified. This analysis focuses on testing whether reliable EPM distances can be obtained for this population. The resulting distances will eventually be compared with independent estimates from the literature. Establishing consistency with these external measurements represents an important step toward applying this methodology to larger samples, with the eventual goal of using ROTSE supernova distances to provide an independent measurement of the local Hubble constant.

Statistical Methodologies For Count Time Series Analysis And Topological Data Analysis Of Medical Images, Yuhyeong Jang

Statistical Science Theses and Dissertations

This dissertation addresses two distinct topics related to count time series analysis and topological medical image analysis, respectively. The first part of the dissertation comprises an application of a count time series model to analysis of US monthly sex trafficking data and development of a new model for multivariate count data that exhibits serial dependence and overdispersion. By imposing a family of multivariate mixed Poisson distributions on the count random vector, the proposed model can accommodate a broad range of overdispersion as well as positive contemporaneous correlations. For maximum likelihood estimation, a computationally feasible EM-type algorithm is derived based on …

Single Fluorogens And Orientation-Localization Microscopy For Quantifying Chemical And Biomolecular Dynamics At The Nanoscale, Yiyang Chen, Yuanxin Qiu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Many chemical systems look uniform only because ensemble measurements average over their most interesting molecules. Electron-transfer rates vary across electrode surfaces; lipid membranes contain nanodomains with distinct packing and fluidity; peptide aggregates exhibit local polymorphism; and biomolecular condensates contain transient networks of interactions that are blurred in ensemble images. A central challenge in chemical imaging is not simply to see smaller structures, but to measure chemical variables such as polarity, redox potential, and molecular confinement at the single-molecule level. In this Account, we describe how fluorogens, molecules whose brightness, blinking, spectral shifts, orientation, rotational mobility, and motion are directly shaped …

Dynamics Of Microscale Droplets In Respiratory Airways, Md Shamser Ali Javed

Mathematics Theses and Dissertations

We investigate trajectories of microscale evaporating droplets in a stagnation point flow near a wall of a respiratory airway. The configuration is motivated by the problem of advection and deposition of microscale droplets of respiratory fluids in human airways during transmission of infectious diseases such as tuberculosis and COVID-19. Laminar boundary layer equations are solved to describe the air flow while the equations of motion of the droplet include contributions from gravity, aerodynamic drag, and Saffman force. Evaporation is accounted for at both the droplet surface and the wall of the respiratory airway and is shown to delay droplet deposition …

Ground To Roof Snow Load Ratio (Gr) Data Release, Brennan Bean, Cooper Nelson, Jesse Wheeler, Scout Jarman, Salam Adil Al-Rubaye, Marc Maguire

Browse all Datasets

This data release provides historical ground-to-roof snow load ratio (GR) datasets used for snow load research and model development. The release includes original referenced datasets, cleaned country specific datasets, and a master dataset that combines Canadian and United States datasets into a standardized format for research and engineering applications.

Data Repository For "The Influence Of Hydrologic And Salinity Conditions On Drought-Tolerant Great Salt Lake Wetland Plant Species" By Samantha Kurkowski And Karin Kettenring, Samantha Kurkowski

Browse all Datasets

This greenhouse experiment investigated the effects of salinity (3 levels) and hydrologic condition (5 levels),  on the cover and biomass of a single mix of 11 native drought- and salt-tolerant species.

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 …

Highly Localized Droplet Clustering In Shallow Cumulus Clouds, Birte Thiede, Michael Larsen, Freja Nordsiek, Oliver Schlenczek, Yewon Kim, Eberhard Bodenschatz, Gholamhossein Bagheri

Michigan Tech Publications

The size and spatial clustering of water droplets in warm clouds influence cloud evolution and radiation properties and thus are of fundamental importance for the Earth’s energy balance and water cycle. Some proposed mechanisms for droplet growth and precipitation initiation in warm clouds require strong droplet clustering. Resolving such clustering on sub-cm scales remains a challenge. The most detailed observations, collected from aircraft, showed weak mm-scale droplet clustering averaged over kilometer scales in stratocumulus clouds. Here we present spatially resolved in-situ holographic measurements from a tethered aerostat, demonstrating that clustering in shallow cumulus clouds is significantly stronger and far more …

Algebraic And Topological Methods In Computational Neuroscience, Trong-Thuc Trang

Electronic Theses and Dissertations 2020 - Present

Neural data is incredibly rich in combinatorial, topological, and geometrical information, reflecting the intricate shape and connectivity of neural firing patterns. To decipher these structures, neuroscience increasingly relies on advanced mathematical tools to analyze neural activity. Here we study (1) neural codes within the poset P_Code of neural codes and (2) the connectivity of neural population activity within the insular cortex when responding to interoceptive information. In (1), we establish combinatorial constructions for all upward covering relations based on what we call “isolated subsets” with supporting theorems and give a slight modification of the existing downward covering relations. We …

Butte Priority Soils Operable Unit Final 2024 Unreclaimed Sites Sampling: Ur-46 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Closing The Awareness–Behavior Gap: A Role-Based Phishing Training Framework For Higher Education, Ranylene O. Olaybal, Ryan A. Olaybal

Journal of Cybersecurity Education, Research and Practice

Phishing remains one of the most persistent cybersecurity threats facing higher education institutions, where diverse user populations and highly connected digital environments increase exposure to social engineering attacks. Although cybersecurity awareness initiatives are widely implemented, high awareness does not always translate into secure behavior. This study examined phishing awareness, phishing-related practices, phishing susceptibility, and phishing experiences among college students, teaching faculty, and administrative staff in a private higher education institution in the Philippines. Using a quantitative cross-sectional design, data were collected from 553 respondents through a validated survey instrument and analyzed using descriptive statistics, one-way analysis of variance, Tukey's honestly …

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 …

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 …

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 …

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.

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 …

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.

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. …

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 …