Digital Commons Network^™

Computationally-Driven Insights Into The Ligand Environments Of Materials For Catalysis And Separations, Stephen Vicchio

All Dissertations

Designing new catalytic and sorption materials is necessary to limit global temperature rise below 1.5 ◦C by 2050, while also meeting global energy demands. Climate change and energy production are not mutually exclusive; global population growth has direct impacts on global energy demands and climate. In both catalysis and adsorption applications, new technologies are needed to address these challenges. Catalysis can provide alternate, low-energy routes for converting low-value gases into higher-value chemical commodities, thus altering our current energy production. Likewise, new sorption materials can capture previously emitted CO₂ from decades of energy production from fossil fuels, thus helping to …

174th Commencement, Fall

Commencement Programs

No abstract provided.

Supporting Schools’ And Teachers’ Use Of Assessment To Inform Learning Of All Students, Ursula Schwantner, Soumaya Maghnouj

Global education monitoring

Issue 5 of the series Using assessment data in education policy and practice: Examples from the Asia-Pacific documents 4 case studies of promising and effective policies or practices on how education systems can better support teachers and schools in effectively integrating assessment practices in the teaching and learning process, to identify and meaningfully address every learner’s needs. In particular, the case studies show how different tools, approaches and policies help promote and reinforce the use of assessment to support more learner-centred and differentiated approaches to teaching and learning. 1. Using the Progressive Achievement approach to develop data-informed schools by Marc …

Evaluating Digital Creativity Support For Children: A Systematic Literature Review, Marte Hoff Hagen, Daniela Soares Cruzes, Letizia Jaccheri, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

Creativity, the process of creating something new and valuable, benefits children by improving their skills and development, encouraging interaction and engagement, and enabling the generation and expression of novel ideas. In recent years, interactive digital tools have emerged to support the user’s creativity in the open-ended creation of new artifacts. However, the question of evaluating the creativity happening in the interplay between children, digital tools, and products is still open. This systematic literature review investigated the evaluations of digital creativity support tools for children and identified 81 peer-reviewed relevant articles from the last 10 years. This research contributes to practitioners …

How Low Can You Go?: Widespread Challenges In Measuring Low Stream Discharge And A Path Forward, Erin C. Seybold, Anna Bergstrom, C. Nathan Jones, Amy J. Burgin, Sam Zipper, Sarah E. Godsey, Walter K. Dodds, Margaret A. Zimmer, Margaret Shanafield, Thibault Datry, Raphael D. Mazor, Mathis L. Messager, Julian D. Olden, Adam Ward, Songyan Yu, Kendra E. Kaiser, Arial Shogren, Richard H. Walker

Geosciences Faculty Publications and Presentations

Low flows pose unique challenges for accurately quantifying streamflow. Current field methods are not optimized to measure these conditions, which in turn, limits research and management. In this essay, we argue that the lack of methods for measuring low streamflow is a fundamental challenge that must be addressed to ensure sustainable water management now and into the future, particularly as climate change shifts more streams to increasingly frequent low flows. We demonstrate the pervasive challenge of measuring low flows, present a decision support tool (DST) for navigating best practices in measuring low flows, and highlight important method developmental needs.

Subduction Initiation Recorded In The Dadeville Complex Of Alabama And Georgia, Southeastern United States, Naomi A. Becker, Freya R. George, George L. Guice, James L. Crowley, Wendy R. Nelson, Joseph F. Browning-Hanson, Supratik Roy, Daniel R. Viete

Geosciences Faculty Publications and Presentations

The Dadeville Complex of Alabama and Georgia (southeastern United States) represents the largest suite of exposed mafic-ultramafic rocks in the southern Appalachians. Due to poor preservation, chemical alteration, and tectonic reworking, a specific tectonic origin for the Dadeville Complex has been difficult to deduce. We obtained new whole-rock and mineral geochemistry coupled with zircon U-Pb geochronology to investigate the magmatic and metamorphic processes recorded by the Dadeville Complex, as well as the timing of these processes. Our data reveal an up-stratigraphic evolution in the geochemistry of the volcanic rocks, from forearc basalts to boninites. Our new U-Pb zircon crystallization data—obtained …

Geophysics-Informed Hydrologic Modeling Of A Mountain Headwater Catchment For Studying Hydrological Partitioning In The Critical Zone, Hang Chen, Qifei Niu, Aida Mendieta, John Bradford, James Mcnamara

Geosciences Faculty Publications and Presentations

Hydrologic modeling has been a useful approach for analyzing water partitioning in catchment systems. It will play an essential role in studying the responses of watersheds under projected climate changes. Numerous studies have shown it is critical to include subsurface heterogeneity in the hydrologic modeling to correctly simulate various water fluxes and processes in the hydrologic system. In this study, we test the idea of incorporating geophysics-obtained subsurface critical zone (CZ) structures in the hydrologic modeling of a mountainous headwater catchment. The CZ structure is extracted from a three-dimensional seismic velocity model developed from a series of two-dimensional velocity sections …

Rapid Evolution Of A(H5n1) Influenza Viruses After Intercontinental Spread To North America, Ahmed Kandeil, Christopher Patton, Jeremy C. Jones, Trushar Jeevan, Walter N. Harrington, Sanja Trifkovic, Jon P. Seiler, Thomas Fabrizio, Karlie Woodard, Jasmine C. Turner, Jeri Carol Crumpton, Lance Miller, Adam Rubrum, Jennifer Debeauchamp, Charles J. Russell, Elena A. Govorkova, Peter Vogel, Mia Kim-Torchetti, Yohannes Berhane, David Stallknecht, Rebecca Poulson, Lisa Kercher, Richard J. Webby

United States Department of Agriculture Wildlife Services: Staff Publications

Highly pathogenic avian influenza A(H5N1) viruses of clade 2.3.4.4b underwent an explosive geographic expansion in 2021 among wild birds and domestic poultry across Asia, Europe, and Africa. By the end of 2021, 2.3.4.4b viruses were detected in North America, signifying further intercontinental spread. Here we show that the western movement of clade 2.3.4.4b was quickly followed by reassortment with viruses circulating in wild birds in North America, resulting in the acquisition of different combinations of ribonucleoprotein genes. These reassortant A(H5N1) viruses are genotypically and phenotypically diverse, with many causing severe disease with dramatic neurologic involvement in mammals. The proclivity of …

College Of Graduate Programs And Honors Studies Newsletter - December 2023, College Of Graduate Programs And Honors Studies, Wright State University

College of Graduate Programs and Honors Studies Newsletter

A five page newsletter created by the College of Graduate Programs and Honors Studies at Wright State University. This newsletter includes a upcoming events, message from the dean, and more.

Iowa Waste Reduction Center Newsletter, December 2023, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Contents:

--- Grain PTE and 6X Reporting Deadlines
--- 2024-2025 Compliance Calendars for Dry Cleaners
--- 2024-2025 Compliance Calendar/Logbook for Bulk Gasoline Plants
--- Alluvial Brewing Company Achieves Gold Certification

Influence Of Thermal Gradient On Mechanical Properties In Fused Deposition Modelling (Fdm) Additive Manufacturing, Cori K. Yancy

All Theses

Fused Deposition Modeling (FDM) is a technique that constructs functional parts by extruding thermoplastic filaments layer by layer. The interplay between thermal dynamics and their subsequent effects on mechanical properties remains a field necessitating further exploration. This study introduced ongoing research focused on unraveling the connection between the thermal gradients in the FDM printing process and the resulting mechanical attributes. The primary objective was to increase quality and functionality of 3D printed components. In pursuit of this objective, a series of carefully planned experiments were devised to systematically vary FDM parameters, including print speed, layer thickness, and nozzle temperature. Through …

Enhancing Short Circuit Fault Detection In Three-Phase Power Systems: A Wavelet-Based Approach, Maysoun Alshrouf

All Theses

This work aimed to improve fault detection accuracy in three-phase power systems, addressing a critical need for reliable and uninterrupted electrical power supply. Existing approaches often fluctuate in accuracy. The study explored the gaps in current literature, emphasizing the need for precise fault detection strategies. The technique to enhance fault detection is an innovative methodology combining MATLAB simulation with Wavelet analysis. This study explored the application of Wavelet transforms, including Daubechies 4, Haar, Symlet 5, and Discrete Approximation Meyer, to the current signals in a three-phase power system. By extracting and comparing the current signal’s detailed coefficients against predefined threshold …

Polluting The Senses: The Impact Of Noise And Light Pollution On Fledgling Movement And Evolution Within The Avian Eye, Margaret C. Mackinlay

Master's Theses

There is more human-generated noise and light today than ever before, a trend tied to ongoing urbanization and with reverberating impacts on a wide range of organisms. While research on these impacts is mounting and particularly plentiful when it comes to birds, there is still much to explore within its effects on avian behavior, fitness, and evolution. In chapter 1, we investigated how fledgling movement is influenced by noise and light pollution. While adult birds have well-documented species-specific responses to these stimuli, fledglings are sorely understudied in this context. We experimentally manipulated light levels and took advantage of an existing …

An Ecological Assessment Of An Endangered Lichen From Central California: Sulcaria Isidiifera, The Splitting Yarn Lichen, Elijah C. Balderas

Master's Theses

Lichens are an underrepresented group of organisms when it comes to both research and conservation efforts. At the same time, lichens face increasing threats from anthropogenic sources including wildfires, climate change and urbanization. With this thesis, I seek to ascertain and publish ecological data on a critically endangered lichen to inform future conservation designations and efforts to preserve and protect the species in perpetuity.

In Chapter 1, I provide an ecological overview of the known range of Sulcaria isidiifera and assess the status of Sulcaria isidiifera via a population count. Sulcaria isidiifera occurs in maritime chaparral habitat in the Los …

Complex Dimensions Of 100 Different Sierpinski Carpet Modifications, Gregory Parker Leathrum

Master's Theses

We used Dr. M. L. Lapidus's Fractal Zeta Functions to analyze the complex fractal dimensions of 100 different modifications of the Sierpinski Carpet fractal construction. We will showcase the theorems that made calculations easier, as well as Desmos tools that helped in classifying the different fractals and computing their complex dimensions. We will also showcase all 100 of the Sierpinski Carpet modifications and their complex dimensions.

Foundations Of Memory Capacity In Models Of Neural Cognition, Chandradeep Chowdhury

Master's Theses

A central problem in neuroscience is to understand how memories are formed as a result of the activities of neurons. Valiant’s neuroidal model attempted to address this question by modeling the brain as a random graph and memories as subgraphs within that graph. However the question of memory capacity within that model has not been explored: how many memories can the brain hold? Valiant introduced the concept of interference between memories as the defining factor for capacity; excessive interference signals the model has reached capacity. Since then, exploration of capacity has been limited, but recent investigations have delved into the …

The Tidal Prism, Viable Eelgrass Habitat, And The Effects Of Sea Level Rise In Morro Bay, Kaden A. Caliendo

Master's Theses

The tidal prism, or the volume of water exchanged from the sea to an estuary from mean low to mean high tide, influences system hydrodynamics and ecological functioning. Since 1884, the tidal prism in Morro Bay, California has been estimated to be decreasing over time due to sedimentation from upstream practices. What is the current tidal prism in Morro Bay and how will that change with sea level rise? How will eelgrass respond to rising sea levels?

For this study, inexpensive tidal gauges were deployed at four locations in Morro Bay from March to August 2023 to measure spatially varying …

The Biological, Physical And Chemical Response Of The Little Creek Watershed To The 2020 Czu Lighting Complex Fire, Natalie Fontana

Master's Theses

This post-fire study was conducted to characterize and observe fire induced changes in physical habitat parameters, water-quality conditions and macroinvertebrate assemblages in the Little Creek watershed, a tributary to Scotts Creek located in Cal Poly’s Swanton Pacific Ranch in Davenport, California. Pre-fire data was collected by a Cal Poly student, John Hardy, for his 2017 thesis. Post-burn bioassessment surveys for this study were repeated at four of the same study sites used by Hardy to provide comparisons to the California Stream Condition Index via a modified version of the State of California’s Surface Water Ambient Monitoring Program protocol. Macroinvertebrates were …

Random Variable Spaces: Mathematical Properties And An Extension To Programming Computable Functions, Mohammed Kurd-Misto

Computational and Data Sciences (PhD) Dissertations

This dissertation aims to extend the boundaries of Programming Computable Functions (PCF) by introducing a novel collection of categories referred to as Random Variable Spaces. Originating as a generalization of Quasi-Borel Spaces, Random Variable Spaces are rigorously defined as categories where objects are sets paired with a collection of random variables from an underlying measurable space. These spaces offer a theoretical foundation for extending PCF to natively handle stochastic elements.

The dissertation is structured into seven chapters that provide a multi-disciplinary background, from PCF and Measure Theory to Category Theory with special attention to Monads and the Giry Monad. The …

Post-Wildfire Effects On A Headwater Stream In The San Bernardino National Forest, Kelley Giron

Electronic Theses, Projects, and Dissertations

Southern California has experienced prolonged drought conditions that have supported frequent wildfires that adversely impact ecosystems, natural resources, and human development. A primary consequence of these events is the impact on water quality and quantity. Of equal concern is evaluating how diverse land use configurations within a watershed can alter the physio-chemical properties of headwater reaches where drought and wildfire conditions are prevalent. To better understand the extent to which wildfires impact water quality and quantity across a headwater watershed, this study investigates wildfire impacts from the 2021 South Fire to Lytle Creek, a headwater stream of the Santa Ana …

Hypothyroid Disease Analysis By Using Machine Learning, Sanjana Seelam

Electronic Theses, Projects, and Dissertations

Thyroid illness frequently manifests as hypothyroidism. It is evident that people with hypothyroidism are primarily female. Because the majority of people are unaware of the illness, it is quickly becoming more serious. It is crucial to catch it early on so that medical professionals can treat it more effectively and prevent it from getting worse. Machine learning illness prediction is a challenging task. Disease prediction is aided greatly by machine learning. Once more, unique feature selection strategies have made the process of disease assumption and prediction easier. To properly monitor and cure this illness, accurate detection is essential. In order …

An Exposition Of The Curvature Of Warped Product Manifolds, Angelina Bisson

Electronic Theses, Projects, and Dissertations

The field of differential geometry is brimming with compelling objects, among which are warped products. These objects hold a prominent place in differential geometry and have been widely studied, as is evident in the literature. Warped products are topologically the same as the Cartesian product of two manifolds, but with distances in one of the factors in skewed. Our goal is to introduce warped product manifolds and to compute their curvature at any point. We follow recent literature and present a previously known result that classifies all flat warped products to find that there are flat examples of warped products …

Classification Of Large Scale Fish Dataset By Deep Neural Networks, Priyanka Adapa

Electronic Theses, Projects, and Dissertations

The development of robust and efficient fish classification systems has become essential to preventing the rapid depletion of aquatic resources and building conservation strategies. A deep learning approach is proposed here for the automated classification of fish species from underwater images. The proposed methodology leverages state-of-the-art deep neural networks by applying the compact convolutional transformer (CCT) architecture, which is famous for faster training and lower computational cost. In CCT, data augmentation techniques are employed to enhance the variability of the training data, reducing overfitting and improving generalization. The preliminary outcomes of our proposed method demonstrate a promising accuracy level of …

Early-Warning Prediction For Machine Failures In Automated Industries Using Advanced Machine Learning Techniques, Satnam Singh

Electronic Theses, Projects, and Dissertations

This Culminating Experience Project explores the use of machine learning algorithms to detect machine failure. The research questions are: Q1) How does the quality of input data, including issues such as outliers, and noise, impact the accuracy and reliability of machine failure prediction models in industrial settings? Q2) How does the integration of SMOTE with feature engineering techniques influence the overall performance of machine learning models in detecting and preventing machine failures? Q3) What is the performance of different machine learning algorithms in predicting machine failures, and which algorithm is the most effective? The research findings are: Q1) Effective outlier …

Lung Lesion Segmentation Using Deep Learning Approaches, Sree Snigdha Tummala

Electronic Theses, Projects, and Dissertations

The amount of data generated in the medical imaging field, especially in a modern context, is growing significantly. As the amount of data grows, it's prudent to make use of automated techniques that can leverage datasets to solve problems that are error-prone or have inconsistent solutions.

Deep learning approaches have gained traction in medical imaging tasks due to their superior performance with larger datasets and ability to discern the intricate features of 3D volumes, a task inefficient if done manually. Specifically for the task of lung nodule segmentation, several different methods have been tried before such as region growing etc. …

Review Classification Using Natural Language Processing And Deep Learning, Brian Nazareth

Electronic Theses, Projects, and Dissertations

Sentiment Analysis is an ongoing research in the field of Natural Language Processing (NLP). In this project, I will evaluate my testing against an Amazon Reviews Dataset, which contains more than 100 thousand reviews from customers. This project classifies the reviews using three methods – using a sentiment score by comparing the words of the reviews based on every positive and negative word that appears in the text with the Opinion Lexicon dataset, by considering the text’s variating sentiment polarity scores with a Python library called TextBlob, and with the help of neural network training. I have created a neural …

Machine Learning For Kalman Filter Tuning Prediction In Gps/Ins Trajectory Estimation, Peter Wright

Electronic Theses, Projects, and Dissertations

This project is an exploration and implementation of an application using Machine Learning (ML) and Artificial Intelligence (AI) techniques which would be capable of automatically tuning Kalman-Filter parameters used in post-flight trajectory estimation software at Edwards Air Force Base (EAFB), CA. The scope of the work in this paper is to design and develop a skeleton application with modular design, where various AI/ML modules could be developed to plug-in to the application for tuning-switch prediction.

Chemistry Instructors’ Perspectives On Incorporating Climate Change Instruction In Undergraduate Chemistry Courses, Patrick Wilson

Dissertations

Education plays an important role in preparing current and future generations for the challenges ahead caused by climate change. The purpose of this dissertation was to examine the educational influence textbooks and undergraduate instructors have on their students. Three studies were carried out to explore these influences on climate change instruction. The first study looked at the extent, type, and location of climate change topics across 24 undergraduate general chemistry textbooks. Gas chemistry concepts were the most prevalent topic connected to climate change. However, the distribution of climate change related material varied considerably across books. The majority of climate change …

Analyzing Trends In Ground-Level Ozone, Keily Hart

Honors Program Theses and Research Projects

In the last few decades, concerns regarding air pollution have led to many new laws and regulations being put into place to mitigate the e↵ects of pollution on the environment and humanity as a whole. This paper analyzes several decades’ worth of ground-level ozone readings in six of the largest metropolitan areas in Texas, using data from the United States Environmental Protection Agency (EPA). These regions include the Austin-Round Rock area, Corpus Christi, the Dallas-Fort Worth-Arlington area, El Paso, the Houston-The Woodlands-Sugar Land area, and the San Antonio-New Braunfels area. We identify trends in these readings using the Jonckheere-Terpstra test. …

Applications Of Survival Estimation Under Stochastic Order To Cancer: The Three Sample Problem, Sage Vantine

Honors Program Theses and Research Projects

Stochastic ordering of probability distributions holds various practical applications. However, in real-world scenarios, the empirical survival functions extracted from actual data often fail to meet the requirements of stochastic ordering. Consequently, we must devise methods to estimate these distribution curves in order to satisfy the constraint. In practical applications, such as the investigation of the time of death or the progression of diseases like cancer, we frequently observe that patients with one condition are expected to exhibit a higher likelihood of survival at all time points compared to those with a different condition. Nevertheless, when we attempt to fit a …