Digital Commons Network^™

The Shorthorn: October 19, 1973

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: October 17, 1973

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: September 28, 1973

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: September 19, 1973

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: September 14, 1973

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: September 12, 1973

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: April 18, 1973

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: April 11, 1973

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: March 7, 1973

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: February 28, 1973

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: December 1, 1972

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: November 3, 1972

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: September 8, 1972

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: March 17, 1972

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: Spetember 3, 1971

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: March 5, 1971

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: February 19, 1971

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

The Shorthorn: December 13, 1970

The Shorthorn Newspaper Collection: 1970s

No abstract provided.

School Safety And Health Policies, Bob Underwood, Erin Mccann

Pediatrics in Practice: A CME Podcast

In this episode, we sit down with Dr. Erin McCann, MD, MPH, attending physician at the Children’s Mercy Primary Care Clinic, to explore the evolving landscape of school safety and health policies. From mental health support and chronic illness management to emergency preparedness and public health mandates, Dr. McCann shares practical insights on how pediatricians can partner with schools and families to create safer, healthier learning environments. Whether you're navigating new legislation or advocating for your patients, this conversation offers timely guidance and actionable takeaways.

Click here to stream the podcast episode.

Understanding Loss To Follow-Up: The Role Of Social Determinants Of Health In Infants Referred After A Positive Newborn Screening – A Quantitative Analysis, Betsy Graham-Moeller Graham-Moeller

Walden Dissertations and Doctoral Studies

Newborn screening (NBS) is a vital U.S. public health initiative that identifies medical conditions shortly after birth. Patients with positive screenings are referred for medical follow-up or evaluation. However, many patients do not receive the recommended long-term follow-up, posing concerns for healthcare providers and public health professionals working to ensure timely treatment and care continuity. Based on the Social Determinants of Health framework, this quantitative, retrospective cohort study aimed to examine demographic and clinical factors associated with follow-up adherence among 691 infants identified through NBS in Colorado and Wyoming. The purpose of the study was to determine whether race, ethnicity, …

Reconciling Harm Reduction Philosophy And Approaches Among Abstinence-Only Substance Abuse Treatment Professionals, Amy Rose Ashton-Williams

Walden Dissertations and Doctoral Studies

Historically, substance use disorder (SUD) treatment in the United States has been firmly grounded in abstinence-only treatment approaches. Harm reduction as a treatment model has gained additional traction. With increased rates of opioid use, overdoses, and advancements in medications for SUDs, harm reduction treatment approaches are becoming more important to improve lives of people who use drugs. Little is known about how counselors who have been educated, trained, and deliver abstinence-based SUD treatment reconcile use of harm reduction into their practice. To address this gap in literature, a generic qualitative study was conducted using the social constructivism theory. A purposive …

Multimodal Emotion Detection And Analysis From Conversational Data, Abhinay Jatoth, Faranak Abri, Tien Nguyen

Faculty Research, Scholarly, and Creative Activity

—Emotion recognition in conversations has become increasingly relevant due to its potential applications across various fields such as customer service, social media, and mental health. In this work, we explore multimodal emotion detection using both textual and audio data. Our models leverage deep learning architectures, including Transformer-based models such as Bidirectional Encoder Representations from Transformers (BERT), Robustly optimized BERT approach (RoBERTa), Audio Spectrogram Transformer (AST), Wav2Vec2), Bidirectional Long Short-Term Memory (BiL-STM), and four fusion strategies that combine features from multiple modalities. We evaluate our approaches using two widely used emotion datasets, IEMOCAP and EMOV. Experimental results show that fusion models …

Assessing University Students’ Self-Reported Vocabulary Learning Strategy Use, Yirgalem Girma

Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan

Learning vocabulary is certainly a vital component of language learning and without this integral component of language communication becomes hardly meaningful. Thus, students are expected to have rich vocabulary power that enables them to communicate successfully via listening, speaking, reading, and writing; it assists students in expressing a range of meanings in various communicative situations for various purposes. This demands students to learn vocabulary using diverse vocabulary learning strategies that assist them in learning (internalizing, storing, recalling, and using) words properly. However, several students barely manage vocabulary learning tasks and/or use appropriate and diverse vocabulary in English classes. Consequently, this …

Gwich'in Athabascan Storybook For Primary Classrooms: Integrating Alaska Native Language And Culture Into Language Arts Curriculum, Lin Vandyke

Education

The problem addressed by this project is the lack of high-quality children’s literature that accurately embodies Alaska Native culture, specifically Gwich’in Athabascan culture, that can be used in primary classrooms. The significance of this topic is the need for materials that Alaska Native students can connect with on a personal level and that can create a greater understanding of Native culture for all individuals. The work was completed in July of 2025. The important implications of this project are the availability of an easy-to-use storybook and connected resources to read with students and have quality discussions about Athabascan language and …

Exploring The Intersection Of Race And Native Speakerism In English Language Teaching: Experiences Of Black African Teachers In Turkey, John Ayodeji Odudele

Linguistics

Research on race and native speaker status in language teaching provides little insight into the experiences of Black African English teachers (BAETs) in the diaspora. To address this gap, this study examines how aspects of BAETs' positionalities - such as race and native speaker status create challenges in their professional and societal lives in Turkey. Data from twelve semi­ structured interviews of BAETs were analyzed using thematic analysis. Findings suggest that race­ related challenges trump language-related ones and that Blackness fundamentally shapes outsiders’ perception and value of BAETs’ linguistic expertise. Even when BAETs possess the same or superior qualifications as …

Investigation Of Dependency Parsing Techniques For Digital Document Analysis Through Deep Learning Approach, Rekah D Ms

Theses and Dissertations

Digital document dependency parsing is a significant task in natural language processing. Dependency parsing supports verification of the grammatical correctness of a sentence besides enabling extraction of relevant documents. Inappropriate extraction of features may result in falsely parsing a document, leading to decreased accuracy. Machine learning methods have been employed to perform feature extraction. However, selecting pertinent features was never achieved which minimizes the time consumption and overhead.

Hence, novel machine learning and deep learning techniques have been designed in our work for accurate and computationally efficient digital document analytics through dependency parsing. Four different contributions have been proposed for …

Design And Development Of Machine Learning And Deep Learning Based Algorithms For Cyberattacks Detection, Abiramasundari S

Theses and Dissertations

E-mail is the fastest mode of communication. It is amongst the most commonly used modes of communication and can be used for both legal and illegal purposes. Many elements that could be useful in detecting email fraud are constantly being investigated. Phishing assaults in which thieves use Internet to trick consumers into visiting fake websites are very common and are causing significant harm to victims. Several methods of filtering phishing emails have been devised but a solution to the problem still evades. One of the attacks addressed in this research is email phishing. Machine learning is a popular and efficient …

Toward A Consensus Model Of Cognitive–Reading Achievement Relations Using Meta-Structural Equation Modeling, Daniel B. Hajovsky, Christopher R. Niileksela, Dawn P. Flanagan, Vincent C. Alfonso, William Joel Schneider, Jacob Robbins

Department of Psychology Faculty Scholarship and Creative Works

Cognitive tests measure psychological constructs that predict the development of academic skills. Research on cognitive–reading achievement relations has primarily been completed with single-test batteries and samples, resulting in inconsistencies across studies. The current study developed a consensus model of cognitive–reading achievement relations using meta-structural equation modeling (meta-SEM) through a cross-sectional analysis of subtest correlations from English-language norm-referenced tests. The full dataset used for this study included 49,959 correlations across 599 distinct correlation matrices. These included correlations among 1112 subtests extracted from 137 different cognitive and achievement test batteries. The meta-SEM approach allowed for increased sampling of cognitive and academic reading …

Master Of Social Work Portfolio, Eryn Eva Robinson

Graduate Student Portfolios, Professional Papers, and Capstone Projects

This portfolio narrative chronicles my professional and personal development throughout my Master of Social Work (MSW) program, reflecting a journey grounded in Indigenous values, trauma-informed practice, and a commitment to social justice. Rooted in my identity as a Native American woman and informed by my grandmother’s survival of the Indian boarding school system, my practice philosophy emphasizes healing-centered engagement, cultural humility, and systemic advocacy. Through diverse practicum experiences, ranging from managing after-school youth programs to clinical work as a Registered Behavior Technician (RBT) supporting children on the autism spectrum, I integrated theoretical knowledge with hands-on practice. I applied frameworks such …

Multi-Layered Framework For Llm Hallucination Mitigation In High-Stakes Applications: A Tutorial, Sachin Hiriyanna, Wenbing Zhao

Electrical and Computer Engineering Faculty Publications

Large language models (LLMs) now match or exceed human performance on many open-ended language tasks, yet they continue to produce fluent but incorrect statements, which is a failure mode widely referred to as hallucination. In low-stakes settings this may be tolerable; in regulated or safety-critical domains such as financial services, compliance review, and client decision support, it is not. Motivated by these realities, we develop an integrated mitigation framework that layers complementary controls rather than relying on any single technique. The framework combines structured prompt design, retrieval-augmented generation (RAG) with verifiable evidence sources, and targeted fine-tuning aligned with domain truth …