Digital Commons Network^™

Trauma And Executive Function: Discovering And Developing Academic Motivation Interventions For Adolescents In Residential Mental Health Treatment, Jamie Jensen

School of Education and Leadership Student Capstone Projects

This capstone project is a curriculum for adolescents in mental health treatment to address the impact of trauma on academic performance and determine interventions for the development of executive function (EF) skills, including metacognition, perseverance, planning, and organization. The project's central question explored how teaching these skills alongside academic standards can impact self-efficacy and academic performance. The project examined trauma's impact on EF and academics, emphasizing EF's role in academic success. Trauma can hinder EF development, affecting working memory, inhibitory control, and cognitive flexibility critical for goal-oriented tasks. The project explored how academic motivation, influenced by mindset and resilience, drives …

Shutting Out Noise And Understanding Artificial Intelligence, Lauren J. Yu

Michigan Law Review

A review of Noise: A Flaw in Human Judgment. By Daniel Kahneman, Olivier Sibony and Cass R. Sunstein, and You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It’s Making the World a Weirder Place. By Janelle Shane.

Parallelized Quadtrees For Image Compression In Cuda And Mpi, Aidan Jones

Senior Honors Theses

Quadtrees are a data structure that lend themselves well to image compression due to their ability to recursively decompose 2-dimensional space. Image compression algorithms that use quadtrees should be simple to parallelize; however, current image compression algorithms that use quadtrees rarely use parallel algorithms. An existing program to compress images using quadtrees was upgraded to use GPU acceleration with CUDA but experienced an average slowdown by a factor of 18 to 42. Another parallelization attempt utilized MPI to process contiguous chunks of an image in parallel and experienced an average speedup by a factor of 1.5 to 3.7 compared to …

Review Of The Williamsburg Avant-Garde: Experimental Music And Sound On The Brooklyn Waterfront, By Cisco Bradley, Theodore B. Gordon

Publications and Research

Book Review of The Williamsburg Avant-Garde: Experimental Music and Sound on the Brooklyn Waterfront, by Cisco Bradley

Enhancing Loan Approval Decision-Making An Interpretable Machine Learning Approach Using Lightgbm For Digital Economy Development, Teuku Rizky Noviandy, Ghalieb Mutig Idroes, Irsan Hardi

Malaysian Journal of Computing (MJoC)

This study aims to enhance loan approval decision-making in the digital economy using an interpretable machine learning approach. The primary research question investigates how integrating an interpretable machine learning approach can improve the accuracy and transparency of loan approval processes. We employed LightGBM, a gradient-boosting framework for loan approval classification, optimized via Random Search hyperparameter tuning and validated using 10-fold cross-validation. We incorporated the Shapley Additive exPlanations (SHAP) framework to address the challenge of interpretability in machine learning. The LightGBM model outperformed conventional algorithms (Decision Tree, Random Forest, AdaBoost, and Extra Trees) in accuracy (98.13%), precision (97.78%), recall (97.17%), and …

...Of Cabbages And Kings, Spring 2024, Emeriti Society, University Of The Pacific

Emeriti Newsletter: "...Of Cabbages and Kings"

"...Of Cabbages and Kings" is the newsletter of the University of the Pacific Emeriti Society. Read more about the Emeriti Society of Pacific by clicking here.

A Generalization Of Neutrosophic Metric Space And Related Fixed Point Results, Fahim Ud Din, Umar Ishtiaq, Lakhdar Ragoub, Khalil Javed, Muhammad Arshad

Neutrosophic Sets and Systems

Neutrosophic set is a generalization of classical sets, fuzzy set, intuitionistic sets etc. A mathematical notion neutrosophic set dealing issues containing inconsistent, indeterminate and imprecise data. In this manuscript, we toss the notion of Neutrosophic b-metric-like spaces and obtain some fixed point results in the sense of Neutrosophic b-metric-like spaces. Our results are improvements of recent results in the existing literature. For the validity of these results some non-trivial examples are imparted.

N-Closure And N-Interior In Neutrosophic Topological Spaces, K. Damodharan, M. Vigneshwaran

Neutrosophic Sets and Systems

Toplology greatly bene ts from the concept of-cloure. Its quiet nature to extended its proper ties in other topological spaces. So, with the concept of quasi-coincidence Ganguly and Saha pioneered and extensively examined the notion of-closure within the domain of fuzzy topological spaces.(FTS). The theory of-closure in intuitionistic fuzzy topological spaces (IFTS) was further extended by Seok Jong Lee and Yeon Seok Eom. In this work, the notion of N-closure in Neutrosophic Topological Spaces (NTS) is put forward and discussed.

Analysis Of Neutrosophic Set, Julia Set In Aircraft Crash, M.N. Bharathi, G. Jayalalitha

Neutrosophic Sets and Systems

A neutrosophic fuzzy set that generalizes the classical set is represented by a closed interval [0,1]. Let us generalize the fuzzy set to the Neutrosophic set, which is defined as three membership functions between interval]-0,1+ [. This paper examines the bird collision problem within a more grounded Neutrosophic framework. The collision between the bird and the aircraft is represented in the Neutrosophic domain as a stationary point because it occurs at a distance too great for any other auditory signal to discern. Numerous methods exist for solving the airplane problem, including a Julia set in complex numbers. Bird collisions resulting …

Neutrosophic Sets And Systems, Vol. 66,2024, Florentin Smarandache, Mohamed Abdel-Basset, Said Broumi

Neutrosophic Sets and Systems

No abstract provided.

1st Place Contest Entry: Examining Students’ Perception Of & Experiences In Stem Course Office Hours, Gabriella Dauber

Kevin and Tam Ross Undergraduate Research Prize

This is Gabriella Dauber's submission for the 2024 Kevin and Tam Ross Undergraduate Research Prize, which won first place. It contains their essay on using library resources, their bibliography, and a summary of their research project on students’ perception of and experiences in their STEM course office hours.

Gabriella is a fourth-year student at Chapman University, majoring in Biological Sciences. Their faculty mentor is Dr. Cassandra Zalman.

The Relationship Between General And Content-Specific Classroom Practices And K-6 Student Math Achievement: A Multi-Method Analysis, Karen Alexander Glueckdert

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Research has suggested that measures of both general classroom observational tools (Classroom Organization and Teacher Emotional/Instructional Support) and content-specific observational tools (Ambitious Math Instruction and Errors and Imprecision) are related to K-6 student math achievement and therefore there is encouragement to use both types of observational measures as part of teacher evaluation. This study aims to provide policy makers, practitioners, and researchers with an overall picture of the expected relationships between the observational measures and K-6 student math achievement to inform decisions, policies, and future research. A multi-method analysis was conducted in which a meta-analytic structural equation model, a quantitative …

Analysis Of State Climate Action Plans: What Influences States To Adopt, Ethan Yaroch

Honors Program: Senior Projects (Public)

Federal-level policies aimed to address and mitigate the effects that will arise from climate change have become an extremely polarizing issue in the United States. Given this policy stalemate, individual states have stepped up to address the national-level shortcomings by publishing state-level Climate Action Plans (CAPs). CAPs mainly consist of emissions mitigation goals and other non-binding policy initiatives that provide a basis for future compulsory legislation. This paper examines whether party identification in the state legislature, public opinion, susceptibility to the risks associated with climate change, and proximity to neighboring states with published CAPs influence states to adopt CAPs. Employing …

Heat Mitigation Impacts Of Agriculture, Greenspace, And Riparian Forest In Albuquerque, New Mexico, Brennan Davis

Water Resources Professional Project Reports

Albuquerque, New Mexico, alongside the larger American desert Southwest, is already living the reality of climate change – temperatures have risen faster than the global average and, left unchecked, will continue to rise at an ever-increasing pace (NOAA 2022, Garfin et al. 2014). Alongside this disproportionate warming, the Southwest has experienced worsening drought which further stresses an already arid system (White et al. 2023, Dunbar et al. 2022). At the intersection of these changes lie a myriad of interrelated consequences for both ecosystems and communities. The urban heat island effect is one of many such consequences and is responsible for …

Building Civic Efficacy In Adolescents Through Civic Zines, Darryl Ashley Owens

MATL Action Research Projects

No abstract provided.

Timing Vocabulary Instruction For English Language Learners: Evaluating The Impact Of Pre- Teaching Vs. Post-Teaching Approaches On Steam Comprehension, Askin Topal

MATL Action Research Projects

No abstract provided.

Growth Mindset And Self-Confidence In Math, Jacqueline Drew Wehe

MATL Action Research Projects

No abstract provided.

Hydrologic Impact Index For The Pinhoti Hiking Trail, Allie Field

Theses

Author note: The author of this thesis is also published under the name Allie Bobo.

This study aimed to identify flood-prone areas along the Pinhoti Trail and Chinnabee Silent Trail in the Talladega National Forest. Using the Hydrology Flood Index layer that was created using several essential data layers, the research aimed to provide campers, hikers, nature enthusiasts, and trail maintenance teams with information about areas at a higher risk of flash flooding. The Hydrology Flood Index layer rates the risk of flooding on a scale of 1 to 4, with level 1 indicating a low risk of flooding and …

Shorting At Long Duration: Impact Of Extended Discharge Capacity On Battery Solid Electrolytes, Ryan C. Hill, Amanda S. Peretti, Leo J. Small, Erik D. Spoerke, Yang-Tse Cheng

Chemical and Materials Engineering Faculty Publications

Long-duration energy storage (LDES) is critical to a stable, resilient, and decarbonized electric grid. While batteries are emerging as important LDES devices, extended, high-power discharges necessary for cost-competitive LDES present new materials challenges. Focusing on a new generation of low-temperature molten sodium batteries, we explore here unique phenomena related to long-duration discharge through a well-known solid electrolyte, NaSICON. Specifically, molten sodium symmetric cells at 110 ° C were cycled at 0.1 A cm−2 for 1–23 h discharges. Longer discharges led to unstable overpotentials, reduced resistances, and decreased electrolyte strength, caused by massive sodium penetration not observed in shorter duration discharges. …

Global Challenges In Accessing Mental Health Services And Addressing The Impact Of Alzheimer’S Disease And Depression, Padmapriya Velupillai Meikandan

Master's Theses (2009 -)

This research project focuses on developing a quantum sensing system that can detect biomarkers associated with health disorders, like Alzheimer’s and depression. Our goal is to create a sensitive and highly selective quantum sensing device using a diamond nitrogen vacancy (NV) center. To train and test our quantum machine learning algorithms we will preprocess data from the available Human Connectome Project dataset. This dataset forms the basis of our quantum-based methods. The core of our project revolves around developing quantum machine learning algorithms that utilize techniques such as Support Vector Machines and neural networks to diagnose health disorders using data …

Development And Validation Of A Vehicle Front Profile Finite Element Model To Evaluate Pedestrian Impacts, James Wolf

Master's Theses (2009 -)

In 2021, there were nearly 7500 pedestrians killed in traffic crashes in the U.S., the highest since 1981. Since the year 2000, Europe and Japan have adopted pedestrian crash protection programs for vehicles and have seen a decline in pedestrian fatalities; the U.S. has not yet adopted pedestrian crash protection and has seen an increase in pedestrian fatalities in that same time. European New Car Assessment Programme (Euro NCAP) outlines a detailed procedure for evaluations of new vehicles for pedestrian safety through headform, upper legform, and lower legform tests. Euro NCAP also uses generic finite element (FE) front-end vehicle models, …

Advanced Machine Learning Approaches For Predicting Mental Health Disorders Following Long Covid Diagnosis, Manoj Purohit

Master's Theses (2009 -)

After the global spread of COVID-19, the enduring effects of Long COVID and its health implications have emerged as a significant global issue, affecting people worldwide. The lingering symptoms post a COVID-19 infection can significantly affect individuals who had previously contracted the virus, exerting considerable influence over their mental well-being. Prolonged recuperation associated with Long COVID has been connected with the emergence of symptoms such as depression and anxiety, all of which can have adverse effects on emotional health. This project delves into an in-depth analysis of healthcare data pertaining to Long COVID from the Froedtert Health (FH) Medical System …

Viscoelastic Properties Of Thoraco-Abdominal Tissue Under Dynamic Compressive Loading, Devin Matthew Wozniak

Master's Theses (2009 -)

Finite element analysis is an effective tool for modeling the mechanical behavior of biologic structures, especially in scenarios where physical experimentation is impractical. The accuracy of these models depends on comprehensive mathematical formulations that describe tissue behavior using parameters derived from laboratory data. Currently there is a shortage of experimental data suitable for detailed parameter estimation. The goal of the current study was to generate a viscoelastic dataset using fresh harvested porcine tissue maintained under in vivo conditions, then provide a detailed constitutive model to capture the complex mechanical response. A sevohydraullic piston with a 5-mm spherical tip indenter was …

Cultivating Confidence: The Impact Of Goal Setting And Self Assessment On Self- Efficacy Among At-Risk Secondary Students In English Language Arts, Stevie Marie Miles Gonzales

Capstone Projects and Master's Theses

If students perceive themselves as successful readers and communicators, then their self-efficacy in the academic arena will shift, increasing motivation and achievement in turn. Interventions established to support self-efficacy among at-risk students may improve their chances of secondary completion and this will have a positive impact not only for students currently in our schools, but also for their future success and the success of our wider communities. This quantitative two group study was designed to examine whether individual goal setting when paired with self assessment could positively impact at-risk secondary -efficacy in ELA for grade 10. Self-efficacy was measured using …

Learning From Data In Dentistry: Summary Of The Third Annual Openwide Conference, Elsbeth Kalenderian, Kawtar Zouaidi, Jan Yeager, Janelle Urata, Alfa Yansane, Bunmi Tokede, D Brad Rindal, Heiko Spallek, Joel White, Muhammad Walji

Faculty, Staff and Student Publications

The overarching goal of the third scientific oral health symposium was to introduce the concept of a learning health system to the dental community and to identify and discuss cutting-edge research and strategies using data for improving the quality of dental care and patient safety. Conference participants included clinically active dentists, dental researchers, quality improvement experts, informaticians, insurers, EHR vendors/developers, and members of dental professional organizations and dental service organizations. This report summarizes the main outputs of the third annual OpenWide conference held in Houston, Texas, on October 12, 2022, as an affiliated meeting of the American Dental Association (ADA) …

Evaluating And Improving The Usability Of A Mhealth Platform To Assess Postoperative Dental Pain, Ana M Ibarra-Noriega, Alfa Yansane, Joanna Mullins, Kristen Simmons, Nicholas Skourtes, David Holmes, Joel White, Elsbeth Kalenderian, Muhammad F Walji

Faculty, Staff and Student Publications

OBJECTIVES: The use of interactive mobile health (mHealth) applications to monitor patient-reported postoperative pain outcomes is an emerging area in dentistry that requires further exploration. This study aimed to evaluate and improve the usability of an existing mHealth application.

MATERIALS AND METHODS: The usability of the application was assessed iteratively using a 3-phase approach, including a rapid cognitive walkthrough (Phase I), lab-based usability testing (Phase II), and

RESULTS: The rapid cognitive walkthrough identified 23 potential issues that could negatively impact user experience, with the majority classified as system issues. The lab-based usability testing yielded 141 usability issues.; 43% encountered by …

Unveiling Gene Interactions In Alzheimer's Disease By Integrating Genetic And Epigenetic Data With A Network-Based Approach, Keith L Sanders, Astrid M Manuel, Andi Liu, Boyan Leng, Xiangning Chen, Zhongming Zhao

Faculty, Staff and Student Publications

Alzheimer’s Disease (AD) is a complex disease and the leading cause of dementia in older people. We aimed to uncover aspects of AD’s pathogenesis that may contribute to drug repurposing efforts by integrating DNA methylation and genetic data. Implementing the network-based tool, a dense module search of genome-wide association studies (dmGWAS), we integrated a large-scale GWAS dataset with DNA methylation data to identify gene network modules associated with AD. Our analysis yielded 286 significant gene network modules. Notably, the foremost module included the BIN1 gene, showing the largest GWAS signal, and the GNAS gene, the most significantly hypermethylated. We conducted …

Digital Health Technologies For High-Risk Pregnancy Management: Three Case Studies Using Digilego Framework, Sahiti Myneni, Alexandra Zingg, Tavleen Singh, Angela Ross, Amy Franklin, Deevakar Rogith, Jerrie Refuerzo

Faculty, Staff and Student Publications

OBJECTIVE: High-risk pregnancy (HRP) conditions such as gestational diabetes mellitus (GDM), hypertension (HTN), and peripartum depression (PPD) affect maternal and neonatal health. Patient engagement is critical for effective HRP management (HRPM). While digital technologies and analytics hold promise, emerging research indicates limited and suboptimal support offered by the highly prevalent pregnancy digital solutions within the commercial marketplace. In this article, we describe our efforts to develop a portfolio of digital products leveraging advances in social computing, data science, and digital health.

METHODS: We describe three studies that leverage core methods from

RESULTS: Scalable social computing models using deep learning classifiers …

Identification Of Novel F2-Isoprostane Metabolites By Specific Udp-Glucuronosyltransferases, Ginger L Milne, Marina S Nogueira, Benlian Gao, Stephanie C Sanchez, Warda Amin, Sarah Thomas, Camille Oger, Jean-Marie Galano, Harvey J Murff, Gong Yang, Thierry Durand

Faculty, Staff and Student Publications

UDP-glucuronosyltransferases (UGTs) catalyze the conjugation of glucuronic acid with endogenous and exogenous lipophilic small molecules to facilitate their inactivation and excretion from the body. This represents approximately 35 % of all phase II metabolic transformations. Fatty acids and their oxidized eicosanoid derivatives can be metabolized by UGTs. F2-isoprostanes (F2-IsoPs) are eicosanoids formed from the free radical oxidation of arachidonic acid. These molecules are potent vasoconstrictors and are widely used as biomarkers of endogenous oxidative damage. An increasing body of evidence demonstrates the efficacy of measuring the β-oxidation metabolites of F2-IsoPs rather than the unmetabolized F2-IsoPs to quantify oxidative damage in …

Social And Behavior Factors Of Alzheimer's Disease And Related Dementias: A National Study In The Us, David Ciciora, Elizabeth Vásquez, Edward Valachovic, Lifang Hou, Yinan Zheng, Hua Xu, Xiaoqian Jiang, Kun Huang, Kelley Pettee Gabriel, Hong-Wen Deng, Mary P Gallant, Kai Zhang

Faculty, Staff and Student Publications

Introduction: Considerable research has linked many risk factors to Alzheimer's Disease and Related Dementias (ADRD). Without a clear etiology of ADRD, it is advantageous to rank the known risk factors by their importance and determine if disparities exist. Statistical-based ranking can provide insight into which risk factors should be further evaluated.

Methods: This observational, population-based study assessed 50 county-level measures and estimates related to ADRD in 3,155 counties in the U.S. using data from 2010 to 2021. Statistical analysis was performed in 2022-2023. The machine learning method, eXtreme Gradient Boosting, was utilized to rank the importance of these variables by …