Digital Commons Network^™

Uncovering Spain's Lost Victims: Can The Continuing Crimes Doctrine Expand The Jurisdiction Of The International Criminal Court?, Kaitlyn Booher

Case Western Reserve Journal of International Law

Throughout Spain’s transition years (1975-1985), the country has maintained an “agreement to forget” and consequently failed to prosecute any perpetrators of crimes during the Franco dictatorship. This Note examines Franco-era forced disappearances in Spain and argues that the ICC has ratione temporis jurisdiction to investigate and prosecute perpetrators under the application of the continuing crimes doctrine, which is consistent with the principle of nullum crimen sine lege. (Abstract from author.)

Development Of Welfare Assessment Strategies For Indonesian Zoos, Yonathan Yonathan

School of Biological and Marine Sciences Theses

Animal welfare assessment is a core element of zoo management, helping zoos achieve positive welfare state for their animals. Welfare should be assessed regularly to evaluate, monitor, and improve the standards of care. The research on welfare assessment and its development process increased after the World Association of Zoos and Aquariums (WAZA) launched the 2023 Animal Welfare Goals, which include mandatory welfare assessment process for national and regional zoo associations. In Indonesia, many zoos don’t have their own welfare assessment and find it difficult to adapt generic tools due to variation in husbandry, resources, and facilities. This project aims to …

Conversations In The Classroom: Increasing Dialogic Inquiry To Dismantle Compliance-Based Teaching And Learning, Jill Rivera

West Chester University Graduate Theses, Dissertations, and Final Projects

Verbal interpersonal communication has been diminishing from the teaching and learning process over the past decade in public-school classrooms. School district administrations mandate teachers to utilize digital learning platforms and standardized tests due to the ease at which this technology can quickly gather data. While the transition to digital platforms and test-based education may be well-intended, the result has often been a decrease in dialogic inquiry-based pedagogy which removes teacher autonomy, student agency, and has negative effects on students’ ability to critically think and effectively engage in communication and instruction. The over-emphasis on collecting data based solely on a digitized …

Patterns Of Inpatient Antibiotic Utilization By Race And Ethnicity At Us Children’S Hospitals, Bethany A. Wattles, Jeffrey I. Campbell, Theresa Kluthe, Yana B. Feygin, Kahir Jawad, Michelle D. Stevenson, Deborah Winders Davis, Jennifer Porter, V. Faye Jones, Matt Hall, Michael J. Smith

Biostatistics Faculty Publications

Background and Objectives: Racial and ethnic variations in antibiotic utilization are well-reported in outpatient settings but little is known about inpatient settings. Our objective was to describe national inpatient antibiotic utilization among children by race and ethnicity. Methods: This study included hospital visit data from the Pediatric Health Information System between 01/01/2022 and 12/31/2022 for patients <20 years. Primary outcomes were the percentage of hospitalization encounters that received an antibiotic and antibiotic days of therapy (DOT) per 1000 patient days. Mixed-effect regression models were used to determine the association of race-ethnicity with outcomes, adjusting for covariates. Results: There were 846,530 hospitalizations. 45.2% of children were Non-Hispanic (NH) White, 27.1% were Hispanic, 19.2% were NH Black, 4.5% were NH Other, 3.5% were NH Asian, 0.3% were NH Native Hawaiian/Other Pacific Islander (NHPI) and 0.2% were NH American Indian. Adjusting for covariates, NH Black children had lower odds of receiving antibiotics compared to NH White children (aOR 0.96, 95%CI 0.94–0.97), while NH NHPI had higher odds of receiving antibiotics (aOR 1.16, 95%CI 1.05–1.29). Children who were Hispanic, NH Asian, NH American Indian, and children who were NH Other received antibiotic DOT compared to NH White children, while NH NHPI children received more antibiotic DOT. Conclusions: Antibiotic utilization in children’s hospitals differs by race and ethnicity. Hospitals should assess policies and practices that may contribute to disparities in treatment; antibiotic stewardship programs may play an important role in promoting inpatient pharmacoequity. Additional research is needed to examine individual diagnoses, clinical outcomes, and drivers of variation.

A Demographic Description Of Children And Adolescents With Concomitant Autism And Anxiety Along With A Comparison Of Receipt Of Psychological Services, Elizabeth Salt, Amanda T. Wiggins, David N. Toupin, Emma Parks, Chizimuzo Okoli, Mary Kay Rayens

Biostatistics Faculty Publications

Objective:(1) Evaluate differences in demographic distributions between those with autism alone and those with autism concomitant with anxiety and (2) assess demographic factors associated with receipt of psychological therapy in patients with autism.Methods:Using deidentified health care claims data, we extracted all encounters among children with the International Classification of Diseases-10-CM for Autism Spectrum Disorder (F84) and flagged those with concomitant anxiety (F41.9). Extracted data included age, sex, race, ethnicity, insurance status, and Rural-Urban Continuum Codes. Current procedural terminology codes for psychological services were extracted. Data were analyzed using Mann-Whitney U tests, χ² tests of association, and logistic regression.Results:Demographic differences …

Clinical Criteria For Limbic-Predominant Age-Related Tdp-43 Encephalopathy, David A. Wolk, Peter T. Nelson, Liana Apostolova, Konstantinos Arfanakis, Patricia A. Boyle, Cynthia M. Carlsson, Nick Corriveau-Lecavalier, Penny Dacks, Bradford C. Dickerson, Kimiko Domoto-Reilly, Brittany N. Dugger, Rebecca Edelmayer, David W. Fardo, Michel J. Grothe, Timothy J. Hohman, David J. Irwin, Gregory A. Jicha, David T. Jones, Claudia H. Kawas, Edward B. Lee, Karen Lincoln, Gladys E. Maestre, Elizabeth C. Mormino, Chiadi U. Onyike, Ronald C. Petersen, Gil D. Rabinovici, Rosa Rademakers, Rema Raman

Biostatistics Faculty Publications

Limbic predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) is highly prevalent in late life and a common co-pathology with Alzheimer's disease neuropathologic change (ADNC). LATE-NC is a slowly progressive, amnestic clinical syndrome. Alternatively, when present with ADNC, LATE-NC is associated with a more rapid course. With the emergence of anti-amyloid therapeutics, discrimination of LATE-NC from ADNC is critical and will lead to greater clinical recognition of amnestic patients without ADNC. Furthermore, co-pathology with LATE-NC may influence outcomes of these therapeutics. Thus there is a need to identify patients during life with likely LATE-NC. We propose criteria for clinical diagnosis of …

Code Status Discussions, Hunter Bechtold, Reagan T. Smith, Peter Wallenhorst, Kaylee Gouge, Sarah Schaefer, Kelsey Karnik, Kristen Mcquerry, Kristen E. Fletcher

Biostatistics Faculty Publications

Introduction: Residents frequently conduct code status discussions (CSDs) with patients, but many report not receiving formal training in this skill. While institutions have attempted to address this, there remains a need for a curriculum that uses standardized patients (SPs), is generalizable to students interested in different medical specialties, and has been tested on a large sample of students. Methods: We trained 192 fourth-year medical students across four different campuses in how to conduct CSDs during one 2-hour workshop as part of their Transition to Residency course in April 2024. Students worked with SPs as part of this workshop. Students at …

A Myostatin Inhibitory Antibody Combined With Insulin, Partially Rescues The Musculoskeletal Phenotype Of Female Insulin-Deficient Diabetic Mice, R. Clay Bunn, Reuben Adatorwovor, Philip D. Ray, Alexander R. Keeble, Christopher S. Fry, Sasidhar Uppuganti, Jeffry S. Nyman, John L. Fowlkes, Evangelia Kalaitzoglou

Biostatistics Faculty Publications

Introduction: Type 1 diabetes is associated with deficits in both skeletal muscle and bone. Inhibition of myostatin, a negative regulator of muscle mass, was explored as a druggable target to improve the musculoskeletal phenotype associated with insulin-deficient diabetes in female mice. Methods: We investigated whether administration of an inhibitory myostatin antibody (MyoAb) in streptozotocin-induced diabetes in female mice is protective for skeletal muscle and bone. DBA/2J female mice were injected with low-dose streptozotocin or with citrate buffer (vehicle). Subsequently, mice were implanted with insulin-containing or vehicle pellets, with groups being randomized to myostatin or control antibody for 8 weeks. At …

Diagnosing Statistical Education Needs Of Health Science Learners, Amy S. Nowacki, Ann M. Brearley, Robert A. Oster, Emily Slade, Katrina L. Devick, Matthew J. Hayat, Sally W. Thurston

Biostatistics Faculty Publications

Many types of health science learners, including clinical and translational scientists, students, researchers, and clinicians, seek to increase their knowledge of biostatistics. These learners are heterogeneous in their field, career stage and career focus. Based on the collective experience of an expert panel with over 115 years teaching statistics to health science learners, we propose a framework for considering the needs of health science learners motivated by their career goals. This framework defines four types of health science learners seeking statistical training: (a) consumers, (b) “milestone makers”, (c) biomedical researchers with statistical support, and (d) biomedical researchers without statistical support. …

Exploring Creative Processes In Elementary Art Education: Memory, Observation, And Imagination, Angela Steuer

Graduate Research Papers

This study explores the factors influencing idea generation and creativity in young students, focusing on 4th graders' engagement using comics as a motivational tool. It examines the roles of memory, observation, and imagination in shaping artistic choices, as well as the impact of teaching strategies, such as structured challenges and personal storytelling, in fostering creativity. This research offers insights into how tailored instructional practices and cognitive processes support the artistic development of elementary students, empowering them to generate original ideas and create meaningful artwork.

Intergenerational Arts In The Classroom: A Win-Win, Audrey Klunenberg

Graduate Research Papers

This paper suggests that intergenerational arts programs, particularly those conducted in public schools, can help participants build empathy, a sense of community and belonging. Evidence of these changes was collected through informal observations during three intergenerational art classes in a first grade classroom, as well as through discussions with participants before and after their participation in the intergenerational arts programming. Empathy and community can be built through carefully planned collaborative art-making opportunities and the effect can be evidenced in the forming of relationships, the absence of behavioral problems, and the building of the facilitator’s personal network. The paper concludes that …

Motivations And Challenges For African International Students In Choosing On-Campus Housing And Transitioning Off-Campus, Francis Dugbartey

Graduate Research Papers

The findings of this qualitative phenomenological study explained the motives and challenges faced by African international students (n = 10) who initially chose to live on-campus and subsequently transitioned to off-campus accommodations. The research was conducted through semistructured interviews with African international students who were currently enrolled at a predominantly White institution in the Midwestern United States, discussing their experiences with housing, cultural adjustment, and financial constraints. Although the initial choices to stay on-campus stem from convenience and institutional support, various challenges pushed the students toward going off-campus. To begin with, the costliness of staying in an institution may be …

Graduate Portfolio, Amber Ellen Hoodjer

Graduate Research Papers

No abstract provided.

Graduate Portfolio, Cody Miller

Graduate Research Papers

No abstract provided.

Intellectual And Developmental Disabilities As A Risk For Child Maltreatment, Maddie Hawley

Graduate Research Papers

The purpose of this study is to examine the relationship between intellectual and developmental disabilities (IDDs) and child maltreatment. Data from the 2022 National Child Abuse and Neglect Data System (NCANDS) from the state of Minnesota was analyzed. The sample was made up of 38,083 reports of child maltreatment, where the average age of the child was 7.66 years. 51.2% of the children in the sample were female, and White children comprised the largest portion of the sample at 39.6%. Results of this study showed that children with IDDs are at an elevated risk of child maltreatment compared to typically …

Survivors Of Childhood Sexual Abuse: The Impact Of Social Support, Cultural Background, And Early Interventions, Alysha Haaland

Graduate Research Papers

Childhood sexual abuse (CSA) is a critical public health issue that leaves enduring psychological, emotional, and social impacts on survivors. This paper examines the interrelated roles of social support, cultural background, and early interventions in promoting long-term resilience and recovery, with a particular focus on male and culturally diverse survivors. Grounded in Trauma and Resiliency Theory, this literature review highlights key protective factors—including emotional, informational, and instrumental support—while exploring how cultural norms, religious beliefs, and systemic stigma shape survivors’ coping strategies and access to care. The paper also evaluates the effectiveness of early interventions such as trauma-focused cognitive behavioral therapy, …

Black Girls In School: The Harmful Effects Of Dehumanization And Disciplinary Inequities, Annika Peterson

Graduate Research Papers

Black girls in the U.S. experience dehumanization through adultification and sexual objectification that impact disciplinary practices in the education system. Adultification stereotypes Black girls as more mature, less innocent, and less in need of protection, which results in harsher disciplinary actions and limited empathy from educators. At the same time, sexual objectification reinforces harmful perceptions of Black girls' sexuality and culpability in their sexual violence victimization. The “Jezebel” and “Angry Black Woman” stereotypes continue to influence how Black girls are perceived as either hypersexual or aggressive. These biases and stereotypes contribute to disproportionate disciplinary measures, particularly subjective infractions like “defiance” …

Sexual And Bystander Sexual Harassment Experiences Among Part-Time Female Employees: Testing An Interactive Model, Erin Powers

Graduate Research Papers

The current research investigated the impact of sexual and bystander harassment on work-related attitudes, work behaviors, and psychological health. Participants included 314 females who worked part-time at their organization. All participants individually completed a computer administered Workplace Experiences Survey assessing various aspects of their work environment including personal and bystander harassment experiences, work-related attitudes (supervisor, coworker, and work satisfaction), work behaviors (work and job withdrawal), and psychological well-being. It was predicted that both direct sexual harassment and bystander harassment experiences would be associated with more negative work attitudes, greater withdrawal behaviors, and poorer psychological health, with bystander harassment moderating the …

Using Analysis Of Teaching And Assessment Practices To Revise Implementation Of A Force Unit In An 8th Grade Science Course, Caleb Christine

Graduate Research Papers

One thing I have noticed from my fellow teachers is a desire to improve how we teach and to engage our students in active learning. As a new teacher I have that same desire. Accomplishing my goal of being an effective teacher while also improving how the material is presented requires an approach that includes evaluating not only how the students are performing, but also how they are responding to my instruction.

I used self reflection journals to keep track of how I was presenting material in my classroom. I also collected information from completion of ungraded assignments and investigations. …

The Impacts Of A Problem-Based Learning Unit On Computational Thinking Skills In A 7th Grade Lego Robotics Classroom, Madison Beeler

Graduate Research Papers

The primary focus of this study was to determine what impact problem-based learning (PBL) has on developing computational thinking skills, self-efficacy, and earth science understanding in a middle school robotics classroom. Twenty-eight students took part in a 36-day instructional unit based on the 5E Learning Cycle. Students explored Martian geology, analyzing rock data collected by the Perseverance rover mission to make connections between landforms, integrating Earth science with computational thinking tasks. Pre and post-test data assessed growth of computational thinking and self-efficacy. Statistical analysis showed significant growth in student self-efficacy, while gains in computational thinking were not statistically significant. Students …

Transforming Lives For Eternity: 2024-2025 Year End Summary, Southern Adventist University

Strategic Plans

Southern Adventist University's Strategic Plan Year End Summary for the year 2024-2025.

Improving Chatbot Interactions Through Ai-Driven Hate Speech Detection: Evolving To A Safer Digital Environment-Poster, Rata Gheorghita, Wellington Mariano

ICT

This project aims to explore how Machine Learning can contribute to a better digital interaction, mainly focusing on environments such as online chats, social media, and customer support as they are now an imperative part of daily communication. With this, concerns around hate speech in digital conversations is critical (Council of Europe, 2024). This study focus on the development of a Hate Speech Language Detection Chatbot using machine learning techniques. The key purpose of the chatbot is to monitor and detect harmful content in real time, reducing the need for manual intervention. The creation and implementation of such a tool …

Exogenous Variables In Time Series Forecasting During Economic Volatility: A Cross-Sector And Cross-Crisis Evaluation., Orla Kavanagh

ICT

Economic disruptions pose challenges for time series forecasting, but also offer opportunities to evaluate the value of exogenous information. This study investigates the role of external indicators during the COVID-19 pandemic and the 2025 U.S. tariff shock, using data from Dell (technology) and Boeing (aerospace/manufacturing). ARIMA, SARIMA, and LSTM models were tested with candidate exogenous variables. Results indicate that the benefit of external signals is highly context-dependent: sector, disruption type, and forecast horizon all influence effectiveness. LSTM models generally excel at longer horizons with exogenous inputs, while ARIMA-based models perform better short-term. Findings emphasize that careful variable selection, ongoing evaluation, …

Simulación Clínica En La Formación De Psicólogos Organizaciones: Burnout Y Acoso Laboral, Patricia Vizuete Escobar, Sara Uceda Gutiérrez, Esther Martínez Miguel, Irene Morueco Moreno

Capítulos de libros

No abstract provided.

Credit Card Fraud Detection., Sonia Ndonga

ICT

This capstone project applies machine learning to detect credit card fraud, addressing a critical financial threat to banks and payment providers. Using an anonymised dataset of 284,807 transactions, which is highly imbalanced with only 0.172% fraudulent cases, three models—Logistic Regression, Random Forest, and Gradient Boosting—were developed and evaluated. The pipeline incorporates data preprocessing, feature engineering, hyperparameter tuning, cross-validation, and interpretability analysis using SHAP values, SHAPASH, and permutation importance. Random Forest achieved the highest performance with an ROC AUC of 0.97 and Average Precision of 0.66. The study also considers fairness, threshold optimisation, and practical deployment strategies, providing a robust automated …

Enhancing Fake News And Rumor Detection Using Metadata, Context, And User Interaction With A Hybrid Gcn-Transformer., Lucas Romulo Zuin Gigli

ICT

The increasing influence of social media has significantly impacted how news spreads among users, making the detection of misinformation, including fake news and rumours, a critical task. Previous research has explored content-based and metadata-driven approaches, while recent advancements have leveraged Graph Neural Networks (GNNs) such as GCNs, GATs, and SAGE to analyse user interactions and propagation patterns. This thesis investigates the effectiveness of a Hybrid Graph-Transformer Convolutional Neural Network (GCN-Transformer) for fake news detection, combining graph-based learning with Transformer attention mechanisms. Through in-depth data analysis and advanced detection techniques, this model aims to enhance predictive performance and mitigate the spread …

Discovering Latent Themes: Mixed-Methods Comparative Analysis Of Topic Extraction And Clustering., Laura Byrne

ICT

This study investigates whether clustering and topic modeling can uncover themes within the 167 verses of the King James Version of the Book of Esther. A standardized preprocessing pipeline was applied, and TF-IDF and sentence-embedding feature spaces were used to evaluate topic extraction (NMF, GSDMM, BERTopic, Top2Vec) and clustering (HDBSCAN, DBSCAN, Gaussian Mixtures, Agglomerative) using coherence, cluster validity, lexical distinctiveness, and cross-model similarity metrics. NMF provided the most interpretable topics, GSDMM yielded compact low-overlap topics, BERTopic offered entity-centered groupings, and Top2Vec highlighted broad thematic regions. Cross-model analysis revealed overlapping motifs, notably decree and banquet themes, but clusters and topics did …

Implementation Of Time Series And Neural Networks For Forecasting Agricultural Prices In The Irish Market: A Comparative Analysis Of Milk, Beef, And Potatoes., César Augusto Núñez

ICT

Agricultural price volatility represents a central challenge for the Irish agri-food sector, affecting the stability of producers, cooperatives, and policymakers. This study aimed to compare three predictive approaches applied to strategic commodities such as milk, beef, and potatoes: a traditional statistical time series model (SARIMA) and two deep learning architectures (RNN and LSTM). Using historical price series collected over a decade, the models were developed and evaluated following a rigorous methodological process that included data preparation, algorithm training, and validation of results using performance metrics widely used in time series research. The findings show that the SARIMA model was most …

Enhancing Uk Electricity Price Forecasting Using Deep Learning., Stephen Cooke

ICT

Accurate short-term electricity price forecasting (EPF) is crucial for efficient operation of the UK’s multi-layered power market, impacting generators, traders, the ESO, and policymakers. Prices are highly volatile and non-linear due to renewables, demand fluctuations, and market coupling across Day-Ahead, Intraday, and Balancing Mechanism venues. Traditional statistical models often fail under such dynamics, while machine learning and deep learning approaches—particularly LSTM, GRU, and hybrid architectures—effectively capture temporal dependencies and exogenous drivers. Empirical evidence shows that these models outperform classical baselines, enabling more accurate scheduling, risk management, and financial savings.

Evaluating The Effectiveness Of Variational Mode Decomposition(Vmd)-Enhanced Hybrid Models For Forecasting Volatile Price And Indicator Time Series., Danny Allen

ICT

Forecasting volatile time series, such as commodity prices and market volatility indices, is critical for financial and operational decision-making. This study evaluates the impact of Variational Mode Decomposition (VMD) on hybrid forecasting models combining ARIMA, GARCH, and LSTM. Using gold, platinum, and VIX datasets, models were assessed via MAE, RMSE, and computational time. Results show that VMD improves ARIMA forecasts, and achieves optimal performance when combined with ARIMA-LSTM using performance weighting reducing MAE by 0.62-3.81 and reducing RMSE by 1.48-6.20. Conversely, VMD integration with ARIMA-GARCH and LSTM decreased accuracy. While VMD enhances predictive performance, it increases computational time substantially, increasing …