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Transport And Fate Of Nitrate In A Saturated Buffer Zone As Assessed With A Chloride Tracer Test, Alhassan Sahad, Eric W. Peterson

Faculty Publications - Geography, Geology, and the Environment

The Upper Mississippi Basin, which includes Illinois, has highly fertile soils and experiences intensive agricultural practices. Although fertile, the soils do not drain well, resulting in the installation of tile-drainage systems. The practices of tile systems coupled with the application of nitrogen-rich fertilizers have led to the excessive export of nitrate from the agricultural fields into surface waters, contributing to eutrophication and the development of hypoxic zones in aquatic environments. Saturated riparian buffer zones (SRBs) have been proposed as a means to reduce the amount of nitrate discharged from tile-drained waters into streams. Previous works show a reduction in the …

4. Developing Media And Information Literacy Through Dialogues About Ai, Rosa Thornley, Dory Rosenberg

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

Inviting students to dialogue about Artificial Intelligence (Al) can help to develop media and information literacy. Instead of establishing restrictive policies, we present a method for instructor-facilitated dialogues to teach students to analyze, evaluate, and interact with generative language models. This recursive inquiry process causes students to critically think about the spectrum of AI capabilities and limitations. Practicing this inquiry habit over time directs students towards intuitively questioning the Al which leads them to govern their own choices when they become rhetorically aware of emerging technologies and how it will affect their own research and writing. For instructors in higher …

1. Navigating The New Frontier Of Generative Ai In Peer Review And Academic Writing, Chris Mayer

Teaching and Generative AI: Pedagogical Possibilities and Productive Tensions

This chapter provides an overview of the current landscape and implications of Generative Al (GenAl) in higher education, particularly focusing on its role in academic writing and peer review. The emergence of GenAl tools such as ChatGPT is a transformative development in education, with widespread adoption at unprecedented speed. Large Language Models such as ChatGPT offer great potential for enhancing education and academic writing but also raise serious ethical concerns and tensions including access and usability, the perpetuation of Standard Academic English, and issues of linguistic justice. There is also the need for new approaches and pedagogies for how to …

Investigating Teacher And Student Perceptions Of The Impact Of Chatgpt In The Classroom, Esther Abla Dorgbefu

Graduate Research Theses & Dissertations

This study was an initial attempt to investigate faculty and student perceptions of the impact of ChatGPT in the classroom. The primary purpose of this study was to conduct a cost-benefit analysis of the opportunities and challenges of ChatGPT in education. The following research questions were investigated to achieve this goal: (a) What fears do faculty have about using ChatGPT in education? (b) What fears do students have about the use of ChatGPT in education? (c) What are the possible benefits and consequences of using ChatGPT from students’ perspectives? (d) What are the possible benefits and consequences of using ChatGPT …

Design And Performance Of Superconducting Switches For Nanowire Detectors In Magnetic Fields, Timothy James Draher

Graduate Research Theses & Dissertations

Superconducting nanowire devices fit a broad spectrum of applications, including particle detection and quantum computing, and their expanding use across various fields highlights their role in the hybridization of superconducting and conventional semiconductor electronics. Despite their potential, the low signal output of these devices raises challenges in scalability and integration, particularly in applications for nuclear and high-energy physics, where resilience in magnetic fields is becoming a critical optimization factor. The superconducting nanowire cryotron (nTron) addresses these issues by providing operational gain and logic switching in superconducting nanowire circuits, demonstrating adaptability to multiple materials. This dissertation focuses on modifying the conventional …

Assessing Fixed-Node Diffusion Monte Carlo For Radical Polymerization Reaction Energetics, Timothy Brian Huber

Graduate Research Theses & Dissertations

The art of quantum chemistry is grounded to the discovery of a time efficient computational method that can capture the essential physics. Historically, the Hartree-Fock method, where an electron moves in the mean field of the other electrons, has provided the orbitals used to construct a single-reference Slater determinant and thus formed the basis for molecular orbital calculations. Kohn-Sham density functionals have become overwhelmingly popular among the chemistry community due to their low computational cost. However, their prediction of thermodynamic properties important in free radical polymerization has shown difficulty due to an artificial delocalization of electron density and spin contamination …

Medium Range Prediction Of U.S. Severe Convective Storms, Robert Fritzen

Graduate Research Theses & Dissertations

Severe convective storms (SCSs) are responsible for billions of dollars of losses in the United States each year through hazards such as large hail, damaging convective wind gusts, and tornadoes. While techniques for forecasting these SCSs have improved over the years, a majority of these improvements focus on short term forecasting and nowcasting techniques. Little work has been done to analyze the recent advances in numerical weather prediction techniques, and to leverage these advances to the prediction of SCSs at the medium range (defined herein as lead-day 4--8). The primary objectives of this dissertation research are to: 1) explore the …

Uniform Convergence Of Deep Neural Networks With Lipschitz Continuous Activation Functions And Variable Widths, Yuesheng Xu, Haizhang Zhang

Mathematics & Statistics Faculty Publications

We consider deep neural networks (DNNs) with a Lipschitz continuous activation function and with weight matrices of variable widths. We establish a uniform convergence analysis framework in which sufficient conditions on weight matrices and bias vectors together with the Lipschitz constant are provided to ensure uniform convergence of DNNs to a meaningful function as the number of their layers tends to infinity. In the framework, special results on uniform convergence of DNNs with a fixed width, bounded widths and unbounded widths are presented. In particular, as convolutional neural networks are special DNNs with weight matrices of increasing widths, we put …

Weed Seed Wizard Scenario - Dormancy Shift In Barley Grass In Balaklava, South Australia, Department Of Primary Industries And Regional Development, Western Australia

Biosecurity research reports

The Weed Seed Wizard is a national collaborative project that uses paddock management information to predict weed emergence and crop losses now and in the future.

The Weed Seed Wizard is a computer simulation tool that:

• applies to all Australian grain growing areas

• helps growers understand and manage weed seedbanks on their farms

• uses farm management records to simulate how different crop rotations, weed control techniques, irrigation, grazing and harvest management tactics can affect weed numbers, the weed seedbank and yields

• uses farm-specific management and site-specific weather

• is multi-species

See www.dpird.wa.gov.au for further information on Weed Seed Wizard.

This South …

Weed Seed Wizard Case Study - Grower From Western Australia’S Central Wheatbelt, Department Of Primary Industries And Regional Development, Western Australia

Biosecurity research reports

The Weed Seed Wizard is a national collaborative project that uses paddock management information to predict weed emergence and crop losses now and in the future.

The Weed Seed Wizard is a computer simulation tool that:

• applies to all Australian grain growing areas

• helps growers understand and manage weed seedbanks on their farms

• uses farm management records to simulate how different crop rotations, weed control techniques, irrigation, grazing and harvest management tactics can affect weed numbers, the weed seedbank and yields

• uses farm-specific management and site-specific weather

• is multi-species

See www.dpird.wa.gov.au for further information on Weed Seed Wizard.

This case …

Weed Seed Wizard Scenario - Herbicide Resistance In Wild Oats In Wagga Wagga, New South Wales, Department Of Primary Industries And Regional Development, Western Australia

Biosecurity research reports

The Weed Seed Wizard is a national collaborative project that uses paddock management information to predict weed emergence and crop losses now and in the future.

The Weed Seed Wizard is a computer simulation tool that:

• applies to all Australian grain growing areas

• helps growers understand and manage weed seedbanks on their farms

• uses farm management records to simulate how different crop rotations, weed control techniques, irrigation, grazing and harvest management tactics can affect weed numbers, the weed seedbank and yields

• uses farm-specific management and site-specific weather

• is multi-species

See www.dpird.wa.gov.au for further information on Weed Seed Wizard.

This New …

Regional Price Index 2023, Department Of Primary Industries And Regional Development, Western Australia

Statistics

The 2023 Regional Price Index (RPI) is the eleventh State Government Index contrasting the cost of a common basket of goods and services at a number of regional locations to the Perth metropolitan region. The RPI is used as the basis for the construction of the public sector district allowance, and by the private sector when considering remuneration packages for remotely located staff.

The RPI provides an insight into differences in regional consumer costs. The 2023 RPI basket of 185 goods and services was priced in 39 regional centres around Western Australia.

The 2023 RPI results show that, overall, prices …

Lack Of Neuromuscular Fatigue Due To Recreational Doubles Pickleball, Eric Martin, Matthew Ritchey, Steven Kim, Margaret Falknor, George Beckham

Kinesiology Faculty Publications and Presentations

Background: The lack of knowledge about physical responses to pickleball creates a clear gap about performance in this sport. The purpose of this study was to investigate neuromuscular fatigue caused by playing doubles pickleball. Methods: Recreational pickleball players (n = 32, mean age = 60.0 years) were recruited to perform sets of four countermovement jumps (CMJs) on a force plate before and after doubles pickleball matches. Results: For players who had not played a match prior to testing, there was a significant learning effect across trials within the baseline set of jumps for five outcomes from the CMJ test, including …

On The Vertex Identification Spectra Of Grids, Reginaldo M. Marcelo, Mark Anthony C. Tolentino, Agnes Garciano, Mari-Jo P. Ruiz, Jude Buot

Mathematics Faculty Publications

No abstract provided.

Id Numbers Of Lobster Graphs, Mark Anthony C. Tolentino, Luis Silvestre Jr, Richwell T. Chan Sim, Amir Jann Erikson Diga, Althea Julia R. Loyola

Mathematics Faculty Publications

No abstract provided.

Can't We Just Use Computers? Initial Efforts On Technology-Enhanced Learning Of Operations Research In A Philippine University, Lester Hao, Jeric C. Briones, Mark Anthony C. Tolentino

Mathematics Faculty Publications

Operations Research (OR) is a required course in any applied math program in the Philippines. It involves complex and computation-heavy algorithms to guide and improve decision-making in organizations and relevant contexts. Despite the advent of software that have automated the computations or the implementation of algorithms, the teaching and learning of OR may still be rife with procedures being performed manually by hand. In this paper, we report on our initial progress on a research project that aims to revise the OR syllabi in one Philippine university, by integrating more technological tools in the teaching and learning of OR for …

Towards A More Engaged Democracy: Using Statistical Methods To Detect Election Fraud In The 2022 Philippine National Elections, Juan Miguel Cardaño, Bryan Patrick Mande, Seth William Tionko, Aldrich Ellis C. Asuncion, Jeric C. Briones

Mathematics Faculty Publications

This paper aims to show how citizens can further participate in the elections, aside from just voting. Given the accusations of fraud, this study demonstrates how existing election fraud detection methods can be used in the 2022 Philippine National Elections (PNE) context. Specifically, histograms known as 2D vote turnout distributions were first utilized to model the frequency of the winner's percentage of votes based on the voter turnout in each electoral unit, with key parameters introduced to detect fraud. Vote turnout distributions were then simulated using parametric models involving the aforementioned fraud parameters, with the goal of replicating the actual …

Pneumothorax Detection And Segmentation From Chest X-Ray Radiographs Using A Patch-Based Fully Convolutional Encoder-Decoder Network, Jakov Ivan S. Dumbrique, Reynan Hernandez, Juan Miguel L. Cruz, Ryan M. Pagdanganan, Prospero C. Naval

Mathematics Faculty Publications

Pneumothorax, a life-threatening condition characterized by air accumulation in the pleural cavity, requires early and accurate detection for optimal patient outcomes. Chest X-ray radiographs are a common diagnostic tool due to their speed and affordability. However, detecting pneumothorax can be challenging for radiologists because the sole visual indicator is often a thin displaced pleural line. This research explores deep learning techniques to automate and improve the detection and segmentation of pneumothorax from chest X-ray radiographs. We propose a novel architecture that combines the advantages of fully convolutional neural networks (FCNNs) and Vision Transformers (ViTs) while using only convolutional modules to …

The Human Affectome, Daniela Schiller, Alessandra N.C. Yu, Nelly Alia-Klein, Susanne Becker, Howard C. Cromwell, Florin Dolcos, Paul J. Eslinger, Paul Frewen, Andrew H. Kemp, Edward F. Pace-Schott, Jacob Raber, Rebecca L. Silton, Elka Stefanova, Justin H.G. Williams, Nobuhito Abe, Moji Aghajani, Franziska Albrecht, Rebecca Alexander, Silke Anders, Oriana R. Aragón, Juan A. Arias, Shahar Arzy, Tatjana Aue, Sandra Baez, Michela Balconi, Tommaso Ballarini, Scott Bannister, Marlissa C. Banta, Nora Murphy, Et Al.

Psychological Science Faculty Works

Over the last decades, theoretical perspectives in the interdisciplinary field of the affective sciences have proliferated rather than converged due to differing assumptions about what human affective phenomena are and how they work. These metaphysical and mechanistic assumptions, shaped by academic context and values, have dictated affective constructs and operationalizations. However, an assumption about the purpose of affective phenomena can guide us to a common set of metaphysical and mechanistic assumptions. In this capstone paper, we home in on a nested teleological principle for human affective phenomena in order to synthesize metaphysical and mechanistic assumptions. Under this framework, human affective …

Adjusting For Participation Bias In Case-Control Genetic Association Studies For Rare Diseases, Le Wang, Ben Fitzpatrick, Zhengbang Li, Clarice Weinberg, Jinbo Chen

Mathematics, Statistics and Data Science Faculty Works

Collection of genotype data in case-control genetic association studies may often be incomplete for reasons related to genes themselves. This non-ignorable missingness structure, if not appropriately accounted for, can result in participation bias in association analyses. To deal with this issue, Chen et al. [7] proposed to collect additional genetic information from family members of individuals whose genotype data were not available, and developed a maximum likelihood method for bias correction. In this study, we develop an estimating equation approach to analyzing data collected from this design that allows adjustment of covariates. It jointly estimates odds ratio parameters for genetic …

Rising Plant Demand Strengthens Nitrogen Limitation In Tidal Marsh, Le Wang, Adam Langley, Bella Yedman, Patrick Megonigal

Mathematics, Statistics and Data Science Faculty Works

Nitrogen (N) is a limiting nutrient for primary productivity in most terrestrial ecosystems, but whether N limitation is strengthening or weakening remains controversial because both N sources and sinks are increasing in magnitude globally. Temperate marshes are exposed to greater amounts of external N inputs than most terrestrial ecosystems and more than in preindustrial times owing to their position downstream of major sources of human-derived N runoff along river mouths and estuaries. Simultaneously, ecosystem N demand may also be increasing owing to other global changes such as rising atmospheric [CO2]. Here, we used interannual variability in external drivers and variables …

Excited State Proton Transfer From Acidic Alcohols To A Quinoline Photobase Can Be Solvated By Non-Acidic Alcohol Solvents, Jonathan Ryan Hunt, Joseph Hecht, Clara Goolsby, Jade Hagihara, Monique Loza, Samantha Del Pozo

Chemistry and Biochemistry Faculty Works

Photobases are a type of molecule that become more basic upon photoexcitation and can therefore be used to control proton transfer reactions with light. The solvation requirements for excited state proton transfer (ESPT) in photobase systems is poorly understood, which limits their applicability. Here, we investigate the solvation of the ESPT reaction using 5-methoxyquinoline (MeOQ), a well-studied photobase with an excited state pKa (pKa*) of approximately 15.1, as a model system. Previous studies have shown that, in addition to the acidic donor that donates a proton to the photoexcited MeOQ, an additional “auxiliary donor” is necessary to solvate the resulting …

Investigation Of Ion Pairing And Clustering Leading To The Nucleation Of Fluorite Using Ion Selective Electrode Potentiometry, Courtney L. Crone

Browse all Theses and Dissertations

Previously, mineral nucleation was described by Classical Nucleation Theory (CNT), a theory based on the thermodynamic properties of bulk materials. However, an alternative model, known as the Prenucleation Cluster Pathway, has been increasingly used to describe nucleation of minerals. This model considers the presence of thermodynamically stable ion clusters known as “prenucleation clusters” (PNCs). In the present research, the nucleation mechanism of calcium fluoride was investigated to identify evidence of PNCs by means of the ion-selective electrode (ISE) method, where a CaCl2 solution was titrated into a NaF solution while investigating the effects of saturation level and the aqueous ratio …

An Ml-Assisted Golden-Free Hardware Trojan Localization And Detection Approach For Trusted Microelectronics, Ashutosh Ghimire

Browse all Theses and Dissertations

Hardware Trojans are malicious circuits, hidden in integrated circuits (ICs) which pose a significant threat to security. Detection of hardware Trojans is important to build trust, verify, and make the semiconductor ICs process secure. The existing hardware Trojan detection methods are generally destructive, require intricate comparisons, or require a long time for reverse engineering. In the initial phase of this study, the substitution of supervised hardware Trojan detection methods in ASICs chips is explored with unsupervised approaches, thereby eliminating the dependence on golden references. The Trojan detection uses a ring oscillator (RO) based on NAND as the power monitor. Frequency …

Gan Hemt And Air Core Magnetics Based Power Converters Evaluations At Cryogenic Temperature, Yuqi Wei, Md Maksudul Hossain, H. Alan Mantooth

Electrical Engineering Faculty Publications and Presentations

Cryogenic power electronics is both advantageous and indispensable in many applications, like deep space probe, military electric vehicle, magnetic resonance imaging etc. Among different semiconductors, the gallium nitride (GaN) high electron mobility transistor (HEMT) is the most promising candidate for cryogenic applications with significant conduction loss and switching loss reductions. Moreover, there is no carrier freeze out effect for the GaN HEMTs, which is applicable in extreme low temperature operating conditions. In this work, the efficiency of GaN HEMTs based power converters with different power levels (from several Watts to several kiloWatts) are evaluated at cryogenic temperature. Three different commercial …

Autonomous Basketball Court Creation Robot, Bryce Haldeman, Tyler Gray, Dalon Vura

Williams Honors College, Honors Research Projects

The Autonomous Basketball Court Outlining System presents a comprehensive solution for precision court marking. Powered by a 24V lithium-ion battery and driven by a single ST microcontroller, the system autonomously marks the outline of a half basketball court using predefined algorithms. User-friendly features include easy loading of marking material, actuated by gravity or a small servo motor depending on material of choice, ensuring intuitive operation. Safety is prioritized, with the servo motor eliminating high-pressure concerns, and the system maintains a controlled speed accounting for user well-being. Two step and direction servo motors enable accurate linear displacement, facilitating straight lines, and …

Mitigating Cyber Espionage: A Network Security Strategy Using Notifications, Claire Headland

Williams Honors College, Honors Research Projects

Network security and its mitigation of cyber espionage is paramount to the confidentiality, integrity, and availability of data within the intelligence field. With the advancing efficacy of social engineering to execute cyber espionage attacks, further measures and fail-safe mechanisms have become necessary. If a malicious actor successfully penetrates the network, suspending confidential data transmissions over the compromised network becomes crucial. However, connected users need a platform to receive security notifications and, therefore, need to know that their continued network use compromises more data. This project eliminates this by achieving two primary objectives: designing a multi- layered, hardened, and segmented network …

Porous Bearing Research Rig, Josh Beranek, Hannah Liggett, Jonathan Lemmon, Brandon Allen

Williams Honors College, Honors Research Projects

Our team has decided to continue the research of fluid bearings, specifically, that of the journal and porous bearing. This will continue off of research currently being done at the University of Akron by graduate student Elizabeth Clifford who has developed a mathematical model for a porous bearing. Our job will be to create a testing rig that will be able to either prove or disprove this model. To do this, the rig will need to be able to take measurements of temperature and pressure at key areas within the bearing. It will also need to be readily capable of …

Mechanics And Dimensions Of Divine Forgiveness, Ransford Danson, Kenneth Appiah Kubi

Journal of Adventist Mission Studies

Central to Christianity is the doctrine of forgiveness, yet no unified understanding or coherent concept of forgiveness exists in Christian discourse. Understandings of the process of forgiveness invariably depend on denominational traditions, beliefs, values, and practices (Worthington et al. 2019). A point of convergence is the view that forgiveness relates to the physical or psychological harm or wrongdoing inflicted by one person on another (Słowikowski 2020:56). There is also agreement that forgiveness is of different types: interpersonal, intrapersonal, and God-to-human (Fincham 2022; Maranges and Fincham 2024; Shah et al. 2024). The first two types constitute human (earthly) forgiveness, and the …

Zero-Shot Cross-Lingual Pos Tagging For Filipino, Jimson Paulo Layacan, Isaiah Edri W. Flores, Katrina Bernice M. Tan, Ma. Regina Justina Estuar, Jann Railey E. Montalan, Marlene M. De Leon

Department of Information Systems & Computer Science Faculty Publications

Supervised learning approaches in NLP, exemplified by POS tagging, rely heavily on the presence of large amounts of annotated data. However, acquiring such data often requires significant amount of resources and incurs high costs. In this work, we explore zero-shot cross-lingual transfer learning to address data scarcity issues in Filipino POS tagging, particularly focusing on optimizing source language selection. Our zero-shot approach demonstrates superior performance compared to previous studies, with top-performing fine-tuned PLMs achieving F1 scores as high as 79.10%. The analysis reveals moderate correlations between cross-lingual transfer performance and specific linguistic distances–featural, inventory, and syntactic–suggesting that source languages with …