Physical Sciences and Mathematics Commons^™

Yukon Dust From Source To Sink: Characterizing The St. Elias Mountains As A High-Latitude Dust Source, Audrey Y. Lemoine

Honors Theses

High-latitude dust is an important, yet poorly understood, component of Earth’s climate system. It impacts weather and albedo by acting as cloud condensation nuclei, directly affects Earth’s radiative balance, and can enhance productivity by supplying nutrients to ecosystems. In order to better understand high-latitude dust dynamics and impacts, we sampled glacial meltwater, surface sediment, and Holocene loess in the Łhù’ààn Mân (Kluane Lake) region of the Yukon Territory, Canada. We found that suspended sediment concentration is correlated with average slope and glaciation within a catchment, and is influenced by river morphology. We present new εNd and ⁸⁷Sr/⁸⁶Sr …

The Future Of Code Style: Learning With Gamified Online Tools, Jacob C. Tjaden

Honors Theses

High-quality code is universally pursued by software developers, and one of the most effective indicators of code quality is code style. However, code style is difficult to teach, particularly to introductory students and programmers who benefit most. In this project, we aim to investigate how online tools can improve and teach Python code style, as well as identify the role of gamification in the process. We build an online platform called Fishy that combines code style appraisal tools and utilizes gamification concepts. Our platform incorporates educational metrics such as a code analysis score and targeted quizzes to assess user performance. …

A Sequential Quadratic Programming Approach To Coupling‐Bounded Non‐Inertial Earthquake Cycle Kinematics With Distance‐Weighted Eigenmodes, Brendan J. Meade, John P. Loveless

Astronomy: Faculty Publications

Geologic and geodetic observations provide constraints on tectonic and earthquake cycle kinematics. Block models offer one approach to integrating the effects of plate rotations, elastic strain accumulation, applied basal displacements, internal block strain, and idealized pressure sources. Here, we describe the construction of block models where spatially variable slip rates are parameterized by distance‐weighted eigenmodes operating over meshes of triangular dislocation elements. This dimensionally reduced model is recast as a quadratic programming problem with upper and lower bounds on both geologic fault slip rates and spatially variable slip deficit rates. We propose iterating over successive quadratic programming estimates with evolving …

Highest Risk Density Region For The Communication Of The Impact Of A Treatment Covariate On The Time-To-Event Distribution, Giacomo Biganzoli, Giuseppe Marano Phd, Patrizia Boracchi Phd

COBRA Preprint Series

Analysis of time-to-event (TTE) data is central to clinical research, yet conventional summary measures like the hazard ratio (HR) and restricted mean survival time (RMST) present significant challenges. The HR is often misinterpreted, and its validity depends on the frequently violated proportional hazards assumption, while the RMST is highly sensitive to the choice of time horizon. This paper introduces two novel, assumption-free estimands to address these limitations: the Highest Risk Density Region (HRDR) and the Highest Net Risk Difference Region (HNRDR).

The HRDR identifies the narrowest time interval containing a pre-specified probability mass of events, directly answering the clinical question: …

Fault And Cyberattack Diagnosis And Handling Via Large Language Models And State Prediction For Manufacturing And Quantum Systems, Jihan Abou Halloun

Wayne State University Dissertations

In the digitalization era and Smart Manufacturing, companies are harnessing the power of artificial intelligence (AI) and machine learning (ML) across multiple sectors, including process engineering optimization, process control and fault detection, to enhance efficiency and engineering decision making. Although AI and ML are widely used in anomaly detection and handling, there are still areas where it has been less explored. One of the major areas where AI’s potential in manufacturing needs to be characterized is with respect to the applications of large language models (LLMs) in manufacturing troubleshooting for fault/attack handling. A second major area where the potential of …

How Do Selected Biomedical And Health Sciences Journals React To Submissions Of Artificial Intelligence (Ai) Assisted Manuscripts?, Misa Mi, Lin Wu, Yingting Zhang, Wendy Wu

Library Scholarly Publications

Background and Objectives: Generative artificial intelligence (GenAI) increasingly impacts research and scholarly communication. Given the evolving application of ChatGPT and other AI tools in scholarly communications, health sciences librarians must become cognizant of any existing journal publishing guidelines for AI-created or assisted manuscripts. The study aims to examine how scholarly biomedical and health sciences journals and publishers respond to submissions of these manuscripts and what requirements or policies have been put in place to guide and instruct authors on AI use.

Methods: We first retrieved and consolidated a list of journals representing disciplines in biomedical and health sciences from four …

Maritime Digitalization And Decarbonization: A Sustainable Future, World Maritime University, Korea Research Institute Of Ships And Ocean Engineering, Korea Maritime Institute

Books

The book with the title “Maritime Digitalization and Decarbonization: A Sustainable Future” is the second major outcome following the publication of the Proceedings of WMU Maritime Week (WMW) 2024.

The purpose of WMU Maritime Week 2024 (WMW) was to convene experts from diverse sectors to discuss contemporary maritime issues, generate practical and academic insights, and contribute to the advancement of the international maritime community. Following the success of WMW 2024, the aim is to deliver a top-notch annual conference in the maritime field, producing practical and academic outputs through in-depth discussions of critical contemporary issues in the maritime field. …

Machine Learning Models For Pancreatic Cancer Survival Prediction: A Multi-Model Analysis Across Stages And Treatments Using The Surveillance, Epidemiology, And End Results (Seer) Database, Aditya Chakraborty, Mohan D. Pant

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Background: Pancreatic cancer is among the most lethal malignancies, with poor prognosis and limited survival despite treatment advances. Accurate survival modeling is critical for prognostication and clinical decision-making. This study had three primary aims: (1) to determine the best-fitting survival distribution among patients diagnosed and deceased from pancreatic cancer across stages and treatment types; (2) to construct and compare predictive risk classification models; and (3) to evaluate survival probabilities using parametric, semi-parametric, non-parametric, machine learning, and deep learning methods for Stage IV patients receiving both chemotherapy and radiation. Methods: Using data from the SEER database, parametric models (Generalized Extreme Value, …

Multi-Attribute Characterization Of Polymeric And Lipid-Based Drug Delivery Systems By Column Switching Liquid Chromatography-Mass Spectrometry, Brady W. Drennan

Chemistry & Biochemistry Dissertations - Archive

Drug delivery systems (DDS) are an increasingly relevant technology, owing to their ability to provide controlled release and to enable the use of otherwise toxic or labile therapeutics. However, these modalities are complex, containing a multitude of species with diverse chemical and physical properties. Their characterization, which involves the assessment of critical quality attributes (CQAs), requires numerous analytical techniques. The high-throughput demands of the biopharmaceutical industry have driven the need to consolidate these characterizations into a single analytical method. Consequently, novel analytical technologies are needed to support multi-attribute characterization. A multimodal liquid chromatography–mass spectrometry (LC–MS) system was developed to facilitate …

Structure–Property Relationships Mediated By Lone Pairs And Vacancies In Oxychalcogenides: A Combined Experimental And Theoretical Study, Hoa Hn Nguyen

Chemistry & Biochemistry Dissertations - Archive

Structure–property relationships in some oxychalcogenide materials are strongly governed by the interplay between stereochemically active lone pairs and anion vacancy formation. Through a combination of density functional theory (DFT), synchrotron and neutron total scattering and optical characterization, this work elucidates how local symmetry breaking, chemical substitution, and vacancy dynamics influence electronic and optical behavior across several lone pair-containing systems. In crystalline TeO₂, all three polymorphs exhibit wide band gaps with Te⁴⁺ 5s² lone pairs contributing significantly near the valence band edge. Oxygen vacancy formation is thermodynamically favorable and induces asymmetric charge redistribution and enhanced polarizability, supporting …

Tallgrass Prairie Center 2024-2025 Highlights, University Of Northern Iowa. Tallgrass Prairie Center.

Annual Reports

Contents:

--- Staff
--- From our Director
--- Iowa Roadside Management: Enhancing our public roadsides
--- Research and Restoration: Native seeds and methods for prairie reconstruction
--- Plant Materials: A prairie pedigree for Iowa’s roadsides and beyond
--- Irvine Prairie: Restoring a piece of the original Iowa landscape
--- Prairie on Farms: Making prairie practical
--- Prairie Roots Project: A deeper appreciation of the prairie ecosystem
--- Green Iowa AmeriCorps: Service members expand TPC capacity
--- A Hidden Gem - UNI's Biological Preserves: A legacy of service and partnership
--- UNI Students at the TPC: Practical experience in support of …

Orientable Quadrilateral Embeddings Of Cartesian Products Of Graphs, Matthew Farnsworth, Max Goskie, Adrian Volpe, Jackson Sayre

SPARK Symposium Presentations

In the spirit of Pisanski (1989) we consider orientable quadrilateral embeddings of Cartesian products of cycles on surfaces. We offer a constructive example of such an embedding of three low-order cycles. Then we show more generally that such embeddings exist for the product of a 2-cycle, and even cycle, and an arbitrary third cycle. We represent our graphs using rotation schemes to show this existence. Use of rotation schemes led to the ultimate characterization of our findings visually, providing conjectures for generalizations of products of three cycles.

Topo-Vm-Unetv2: Encoding Topology Into Vision Mamba Unet For Polyp Segmentation, Diego Adame, Jose Angel Nunez, Fabian Vazquez Jr., Nayeli Gurrola, Huimin Li, Haoteng Tang

Computer Science Faculty Publications

Convolutional neural network (CNN) and Transformer-based architectures are two dominant deep learning models for polyp segmentation. However, CNNs have limited capability for modeling long-range dependencies, while Transformers incur quadratic computational complexity. Recently, State Space Models such as Mamba have been recognized as a promising approach for polyp segmentation because they not only model long-range interactions effectively but also maintain linear computational complexity. However, Mamba-based architectures still struggle to capture topological features (e.g., connected components, loops, voids), leading to inaccurate boundary delineation and polyp segmentation. To address these limitations, we propose a new approach called Topo-VM-UNetV2, which encodes topological features into …

Congestion Mitigation For Foraging Robot Swarms Using Spiral Path Strategies, Arturo Gonzalez, Qi Lu

Computer Science Faculty Publications

Swarm robotics offers robust and scalable solutions for tasks such as foraging, but congestion near central collection zones remains a critical challenge, especially with increasing swarm sizes. Traditional solutions, such as static path planning or local repulsion-based methods, often fail to prevent interrobot collisions or bottlenecks near the collection zones. This research presents a comparative study of three strategies to mitigate congestion when returning resources to the central collection zone. The research herein focuses on tightly packed environments where, in theory, robots should follow a preplanned spiral, either ad-hoc, square, or circular, with congestion detection as described in the first …

Robust Mitigation Strategy For Misleading Pheromone Trails In Foraging Robot Swarms, Ryan Luna, Qi Lu

Computer Science Faculty Publications

This study advances the security of swarm robotics by examining the resilience of stigmergic communication in foraging robot swarms against deceptive strategies. We specifically investigate the swarm’s vulnerability to attacks via misleading pheromone trails laid by detractor robots, which significantly hinder foraging performance. Through simulations, we evaluated the adverse effects of such attacks on resource collection and forager capture rates, highlighting a notable decline as the percentage of detractors increases. To counter these threats, we implement a robust defense mechanism utilizing DBSCAN for density-based clustering of pheromone trails, complemented by a cluster grouping method that effectively isolates batches of detractors …

Σ-Ary, Minnesota State University Moorhead, Mathematics Department

Math Department Newsletters

No abstract provided.

Topographic Forcing Of Submesoscale Instability In The Antarctic Circumpolar Current, Laur Ferris, Donglai Gong, John Klinck

CCPO Publications

Subpolar frontal zones are characterized by energetic storms, intense seasonal cycles, and close connectivity with surrounding continental shelf topography. At the same time, predicting the ocean state depends on appropriate partition of resolved and parameterized dynamics, the latter of which requires understanding the dynamical processes generating diffusivity throughout the water column. While submesoscale frontal instabilities are shown to produce turbulent kinetic energy (TKE) and mixing in the surface boundary layer (SBL) of the global ocean, their development in complex dynamical regimes (e.g., elevated preexisting turbulence, large ageostrophic shear, or in proximity to topographic boundaries) is less understood. This study investigates …

Fewer Wetlands, More Drainage: Forensic Mapping Of Wetland Loss And Drainage Alteration Illustrates The Hydrological Transformation Of Coastal Watersheds, Kai C. Rains, Seanacy A. Lawlor, Edgar J. Guerron-Orejuela, Shawn M. Landry, W J. Kleindl, Mark C. Rains

School of Geosciences Faculty and Staff Publications

Land use-land cover (LULC) change is widely implicated in coastal water quality degradation, but we often lack understanding of how LULC change has varied spatiotemporally because so much change occurred before the advent of modern mapping. In this study, we overcome this challenge by using forensic mapping techniques of LULC change over the past 175 years in coastal watersheds on the Atlantic Coast of Florida, USA. We benchmark historical mapping products to modern mapping standards using historical products. These include maps and notes from the Public Land Survey System, military campaigns, and navigation surveys from the nineteenth century, and aerial …

Estimating Pedestrian Crossing Times At Scramble Crossings Via Machine Learning And Agent-Based Modeling, Sho Takami

CURE Proceedings

Scramble crosswalks differ from conventional crosswalks in their ability for pedestrians to cross diagonally. This research compares the average crossing times and investigates the walking behaviors that pedestrians adopt to produce the speediest times in the two crosswalk configurations. Identification of the most efficient set of walking behaviors is done through an agent-based model, whereas producing polynomials relating crossing times to the most prominent walking behaviors is done through regression algorithms in machine learning. With the combination of these two approaches, it is revealed that pedestrians must adopt a relaxed walking style to make each crosswalk configuration efficient. Additionally, between …

Local-Neutrosophic Logic And Local-Neutrosophic Sets: Incorporating Locality With Applications, Florentin Smarandache, Takaaki Fujita

Branch Mathematics and Statistics Faculty and Staff Publications

The study of uncertainty has been a significant area of research, with concepts such as fuzzy sets [87], fuzzy graphs [51], and neutrosophic sets [58] receiving extensive attention. In Neutrosophic Logic, indeterminacy often arises from real-world complexities. This paper explores the concept of locality as a key factor in determining indeterminacy, building upon the framework introduced by F. Smarandache in [73]. Locality refers to processes constrained within a specific region, where an object or system is directly influenced by its immediate surroundings. In contrast, nonlocality involves effects that transcend spatial or temporal boundaries, where changes in one location have direct …

Thermo-Rheological And Tribological Properties Of Low- And High-Oleic Vegetable Oils As Sustainable Bio-Based Lubricants, Abiodun Saka, Tobechukwu K. Abor, Anthony C. Okafor, Monday U. Okoronkwo

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Vegetable oil-based lubricants have attracted increased research attention in recent decades as sustainable alternatives to conventional petroleum-based lubricants in metal machining. However, more studies are required to fully elucidate the thermo-rheological and tribological properties. This study presents an investigation of the thermo-rheological and tribological properties of different vegetable oils, including low- and high-oleic soybean oil, high-oleic sunflower, safflower, and canola oils. The lubricity, and evolution of viscosity and thermodynamic properties as a function of temperature were investigated to obtain important parameters including the viscosity index, flow behavior index, flow activation energy, specific heat capacity, thermal conductivity, coefficient of friction, contact …

F-Layer Parameters Derived By Airglow Emissions At Pituffik Sb, Greenland, Jessica Norrell, Ivana Molina, Michael Negale, Jeffrey Holmes

Space Dynamics Laboratory Publications

Atomic oxygen airglow has long been used as tracer for the peak height and electron density of the F-layer (e.g. Sahai et al., 1981). Tinsley and Bittencourt (1975) described a method by which OI airglow is used to determine F-layer parameters. They found that the square root of the column emission rate of an optically thin layer created by radiative recombination emission was proportional to the peak electron density of the F-layer.

An all-sky imager (ASI) was recently installed at Pituffik, Greenland (76.51˚N, 68.74˚W), with four filters relevant to this study: 5725, 6300, 7715 and 7774 Å. We have used …

Software Management, Space Dynamics Laboratory

Space Dynamics Laboratory Publications

Agenda

1. Software Organization Methods
2. Example Software Workflow
3. Small Sat Specific Tips

Requirements And C&Dh Design, Space Dynamics Laboratory

Space Dynamics Laboratory Publications

• What is it?
• Processor Selection
• CDH Hardware
• OS Selection
• Memory - Radiation
• Memory - Radiation Mitigation
• Memory - Partitions
• Memory - File System
• System Startup
• Startup Stages
• Software Start-up
• Serial Protocol
• I2C / One Wire Communication Tips
• Fault Handling: Watchdog Timer
• CDH Watchdog (Simple)
• CDH Watchdog (Use Case)
• Watchdog Timer Tips
• Synchronizing and Managing Time

Radiation Hardness Drivers For Mission Success – What We Have Learned, Space Dynamics Laboratory

Space Dynamics Laboratory Publications

RHA consists of all activities undertaken to ensure that the electronics and materials of a space system perform to their design specifications throughout exposure to the mission space environment

Communications (Comm) Subsystem: Smallsat Antennas, Jim White

Space Dynamics Laboratory Publications

• A Practical Approach to SmallSat and Cubesat Antennas
• Antennas Designed Using Requirements
• Antenna Requirements
• Systems Engineering is Required
• What is a Radio Wave?
• What is an Antenna?
• Best Practices
• Testing
• Summary

Deep Learning Method For Image Processing In Cold Atom Experiments, Joshua Wilson, Robert Leonard, Jacob Morrey, Issac Peterson, Francisco Fonta, Spencer Olson

Space Dynamics Laboratory Publications

“Ideal” Absorption Imaging

Not always simple in practice

Understanding Physiological Responses For Intelligent Posture Detection Using Wearable Technology, Chaitanya Vardhini Anumula, Tanvi Banerjee, Anuradha Oak

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

This study investigates the physiological impact of Iyengar yoga at the pose-level using EmbracePlus wearable smartwatch, for data recording and personalized yoga pose detection for tracking.

Generative Ai (Gan & Vae) In Motion Sickness Research, Harigovind Harikumar, Tomojit Ghosh

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

No abstract provided.

A Systematic Study Of Freezing Behavior In Earthworms In Response To Auditory And Vibratory Stimuli, Navjot Singh, A. Burton, Dragana Ivkovich Claflin

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

While earthworms have largely been studied for their role in eliminating toxic metals from soil, less is known about their behavior overall. Previous work from our lab found that a predator-like auditory stimulus (grunting) reliably induced fear-related freezing behavior (Worthen et al., 2024). The present studies further explore earthworm behaviors in response to audio-vibratory stimuli. In Experiment 1, we manipulated amplitude levels and speaker location to examine the parameters needed to reliably induce a freezing fear response to the grunting sound. It was hypothesized that when the speaker was touching the apparatus and producing an added mechanical vibration, there would …