Digital Commons Network^™

Shifting Mediates Gendered Racial Microaggressions And Perceived Racism Among Asian American Women, Glenn Gamst, Christine Ma-Kellams, Lawrence S. Meyers, Leticia Arellano-Morales

Faculty Research, Scholarly, and Creative Activity

Introduction: Microaggressive attacks on Asian American women increased during the COVID-19 pandemic. The present study tested whether Asian American women's shifting, a coping strategy employed by some women of color to alter their self-presentation in response to perceived racism, mediated the association between gendered racial microaggressions and self-perceived subtle and blatant racism. Methods: A convenience sample of 253 Asian American adult women completed the gendered racial microaggressions scale for Asian American women (GRMSAAW), the Asian American women's shifting scale (AsAWSS), and the subtle and blatant racism scale for Asian American college students (SABR-A2). Results: Results from a structural equation model …

Boycotting Vs. Canceling: Exploring Consumer Activism Against Corporations, Erica Buchman

Student Theses and Dissertations

The purpose of this thesis is to establish the difference between boycotting and canceling a corporation and what compels consumers to act. Consumer activism attempts to hold companies to account when a line, be it arbitrary or rational, is crossed, and these attempts are not always successful. However, when enough social pressure is exerted on a company via boycotting, depending on the wrongful act committed, accountability and change can be possible. I want to determine what some of the factors are that could compel customers to engage in consumer activism or boycott against a corporation and whether a corporation that …

Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study, Haben Yhdego, Christopher Paolini, Michel Audette

Electrical & Computer Engineering Faculty Publications

Real-time fall detection using a wearable sensor remains a challenging problem due to high gait variability. Furthermore, finding the type of sensor to use and the optimal location of the sensors are also essential factors for real-time fall-detection systems. This work presents real-time fall-detection methods using deep learning models. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. First, we developed and compared different data-segmentation techniques for sliding windows. Next, we implemented various techniques to balance the datasets because collecting fall datasets in the real-time setting has …

Technology Adoption Of Computer-Aided Instruction In Healthcare: A Structured Review, Queenie Kate Cabanilla, Frevy Teofilo-Orencia, Rentor Cafino, Armando T. Isla Jr., Jehan Grace Maglaya, Xavier-Lewis Palmer, Lucas Potter, Dave E. Marcial, Lemuel Clark Velasco

Electrical & Computer Engineering Faculty Publications

Computer-Aided Instruction (CAI) is one of the interactive teaching methods that electronically presents instructional resources and enhances learner performance. In health settings, using CAI is one of the important ways to improve learners' knowledge and usefulness in their healthcare specialization yet there is still a lack of research that offers a comprehensive synthesis of investigating into the adoption of CAI in healthcare. This research aims to provide a comprehensive review of related literatures on the enablers and barriers for technology adoption of CAI in healthcare. 31 journals were analyzed and revealed that several studies were utilizing the Unified Theory of …

Comparison Of Machine Learning Methods For Classification Of Alexithymia In Individuals With And Without Autism From Eye-Tracking Data, Furkan Iigin, Megan A. Witherow, Khan M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Alexithymia describes a psychological state where individuals struggle with feeling and expressing their emotions. Individuals with alexithymia may also have a more difficult time understanding the emotions of others and may express atypical attention to the eyes when recognizing emotions. This is known to affect individuals with Autism Spectrum Disorder (ASD) differently than neurotypical (NT) individuals. Using a public data set of eye-tracking data from seventy individuals with and without autism who have been assessed for alexithymia, we train multiple traditional machine learning models for alexithymia classification including support vector machines, logistic regression, decision trees, random forest, and multilayer perceptron. …

Social-Engineering, Bio-Economies, And Nation-State Ontological Security: A Commentary, Brandon Griffin, Keitavius Alexander, Xavier-Lewis Palmer, Lucas Potter

Electrical & Computer Engineering Faculty Publications

Biocybersecurity is an evolving discipline that aims to identify the gaps and risks associated with the convergence of Biology (the science of life and living organisms) and cybersecurity (the science, study, and theory of cyberspace and cybernetics) to protect the bioeconomy. The biological industries’ increased reliance on digitization, automation, and computing power has resulted in benefits for the scientific community, it has simultaneously multiplied the risk factors associated with industrial espionage and the protection of data both commercial and proprietary. The sensitive and potentially destructive power of this data and its access inherently poses a risk to the national and …

Risk Of Position-Based Concussions Among Collegiate Men And Women Soccer Players, Devin Hauenstein

Cal Poly Humboldt theses and projects

Limiting the incidence of concussions has become a foremost concern among collegiate athletes and coaches. This study aimed to determine if the soccer position played, and minutes played during a game predict the incident of concussion among college soccer players. If concussion risk can be predicted, it may lead to mitigating actions to minimize risks. Data from 208 male and female soccer players from the North Coast Concussion Program (NCCP) were assessed to predict the incidence of concussion based on total minutes played and position(s) played. A logistic regression analysis and predictive modeling technique were used to determine whether the …

A Test Of Subjective Versus Objective Language Proficiency: An Investigation Of Age Of Acquisition And Exposure In Multilinguals, Anastina B. Steiber

Cal Poly Humboldt theses and projects

This research used the BEST dataset gathered in 2017 by de Bruin and colleagues, which contains information gathered from 650 multilingual participants (435 female, Mage = 25.02) from the Basque Country at the Basque Center on Cognition, Brain and Language (BCBL). Multilingual individuals may have different levels of proficiency in each language they speak, and there are various factors that can influence proficiency. Such factors include the age at which they begin learning a language and how much exposure they have to the language. Proficiency can be assessed both subjectively (personal perception of proficiency) and objectively (observed and/or measured …

Extremism In America: Explaining Political Extremism Using Uncertainty-Identity Theory, Natasha A. La Vogue

Cal Poly Humboldt theses and projects

Navigating a post-pandemic society, climate-change, political conflict and international wars have become part of most people’s daily existence. These crises are sources of societal and personal uncertainty. An effective method of uncertainty reduction comes from people’s entrenched group memberships (e.g. nation, political party). Unfortunately, groups with extreme norms and ideologies provide rigid structures that aid in uncertainty reduction. From white nationalists to anti-fascists, the political arena is tumultuous to the point of explosion. These eruptions can be violent, even deadly, and are becoming too familiar and recognizable. Extremism poses both international and domestic threats. There is no nation or society …

Dining Layout Effects On Attendance, Communication, And Happiness In Older Adults, Juliana Lia Bertolucci

Cal Poly Humboldt theses and projects

Our growing national age and the unique challenges presented by the COVID-19 pandemic stress the importance of conducting applied research that identifies effective systems of support for older adults as they age. Behavioral Gerontology is a promising field that applies behavior-analytic procedures to age-related issues. The current behavioral research has primarily focused on older adults in assisted living or nursing homes with major neurocognitive disorders. The current study hopes to add to behavioral gerontological research by applying previous research methods to novel populations. Direct observations were used to examine the effects of manipulating the physical dining layouts on the attendance, …

Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance, Kaushik Roy, Manas Gaur, Misagh Soltani, Vipula Rawte, Ashwin Kalyan, Amit Sheth

Publications

Current Virtual Mental Health Assistants (VMHAs) provide counseling and suggestive care. They refrain from patient diagnostic assistance because of a lack of training on safety-constrained and specialized clinical process knowledge (Pro-Know). In this work, we define ProKnow as an ordered set of information that maps to evidence-based guidelines or categories of conceptual understanding to experts in a domain. We also introduce a new dataset of diagnostic conversations guided by safety constraints and ProKnow that healthcare professionals use (ProKnow-data). We develop a method for natural language question generation (NLG) that collects diagnostic information from the patient interactively (ProKnow-algo). We demonstrate the …

Acm Web Conference 2023, Usha Lokala, Kaushik Roy, Utkarshani Jaimini, Amit Sheth

Publications

Improving the performance and explanations of ML algorithms is a priority for adoption by humans in the real world. In critical domains such as healthcare, such technology has significant potential to reduce the burden on humans and considerably reduce manual assessments by providing quality assistance at scale. In today’s data-driven world, artificial intelligence (AI) systems are still experiencing issues with bias, explainability, and human-like reasoning and interpretability. Causal AI is the technique that can reason and make human-like choices making it possible to go beyond narrow Machine learning-based techniques and can be integrated into human decision-making. It also offers intrinsic …

Tutorial - Shodhguru Labs: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

Tutorial - Shodhguru Labs: Optimization And Hyperparameter Tuning For Neural Networks, Kaushik Roy

Publications

Neural networks have emerged as a powerful and versatile class of machine learning models, revolutionizing various fields with their ability to learn complex patterns and make accurate predictions. The performance of neural networks depends significantly on the appropriate choice of hyperparameters, which are critical factors governing their architecture, regularization, and optimization techniques. As the demand for high-performance neural networks grows across diverse applications, the need for efficient optimization and hyperparameter tuning methods becomes paramount. This paper presents a comprehensive exploration of optimization strategies and hyperparameter tuning techniques for neural networks. Neural networks have emerged as a powerful and versatile class …

A Structured Narrative Prompt For Prompting Narratives From Large Language Models: Sentiment Assessment Of Chatgpt-Generated Narratives And Real Tweets, Christopher J. Lynch, Erik J. Jensen, Virginia Zamponi, Kevin O'Brien, Erika Frydenlund, Ross Gore

VMASC Publications

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent-based models and simulations consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Simulated agents generate large volumes of data and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents' perspectives on key life events by providing natural language narratives. However, these narratives should be factual, transparent, and reproducible. Therefore, we present a structured narrative prompt …

Reshaping The Narrative, Crystal Little Owl

Graduate Student Portfolios, Professional Papers, and Capstone Projects

No abstract provided.

The Commercialization And Imposed Voices Of Femininity In The Summer I Turned Pretty, Danielle Mcclelland

Theses, Dissertations and Culminating Projects

This essay seeks to explore and analyze the novel The Summer I Turned Pretty by Jenny Han. The novel’s ability to maintain relevance as a piece of popular YA literature despite its release over ten years ago makes it an interesting title to study because it demonstrates the concept of a “formulaic text,” which is defined as having, “...simple syntax, frequent repetition, and explicit authorial interpretations” (Smith 31). Additionally, Han’s novel displays the commercialization of femininity and enforces the common heteronormative relationship narrative displayed in this strain of romantic fiction. This essay aims to explore these social phenomena and how …

Sylvia Plath As A Confessionalist Writer : The Queen Bee, Alexandra Tangarife

Theses, Dissertations and Culminating Projects

Sylvia Plath is a renowned Confessionalist poet from the early-mid 20th century in America. She frequently compares to her predecessor, Robert Lowell, and her friend and colleague, Ann Sexton. Confessionalism was an emotionally authentic form of poetry that split off from prior poetry, such as Modernism. Modernist founder T.S Eliot wrote in his “Tradition and The Individual Talent,” “Poetry is not a turning loose of emotion, but an escape from emotion; it is not the expression of personality, but an escape from personality” (1). Despite this mentality, Confessionalists addressed the elephant in the room: the fragmented and emotionally disturbed nation. …

A Black Prometheus Among The Gods: Illuminating African American Literary Tradition In Sam Greenlee's The Spook Who Sat By The Door, Kenneth L. Rainey Iii

Cal Poly Humboldt theses and projects

In his hard-hitting novel The Spook Who Sat by the Door Sam Greenlee aims to help his target African American audience to succeed and thrive as their true selves with the novel functioning as a guide to resisting the ever-present physical and spiritual threat faced daily. On the one hand the novel functions as a manual for civil uprising, but underneath that surface, Greenlee argues that true African American resistance comes through nurturing self-determination, self-love, and self-esteem. This project also argues that Spook ought to be located closer to the center of the African American literary canon and provides comparisons …

Indigenous Women In Active Drug Abuse Recovery: An Analysis Of Native And Non-Native Programs, Raquel J. Muñoz

Cal Poly Humboldt theses and projects

In general, much has been written on the experiences of prototypical women in drug recovery programs, however there is only a scarcity of research on the experiences of rural women of color in drug recovery programs. Very few Northern American cultures had experience with alcohol before the first wave of European settlers. Responses to intergenerational trauma faced by Native women include substance abuse, depression, anxiety, low self-esteem, suicidal thinking, and more. Due to socioeconomic disadvantages drug and alcohol abuse tends to be a coping mechanism for many Native American women. Drawing on the narratives of ten Indigenous women who are …

Prototypicality Threat And Intergroup Threat Theory: Support For Blm Using Militant Or Peaceful Language, Jordan C. Mcdowell

Cal Poly Humboldt theses and projects

Black Lives Matter (BLM) symbolizes the need to recognize the humanity of Black lives and the systemic discrimination contributing to the murders of unarmed Black Americans at the hands of police. While there were some white Americans who participated in the demonstrations during the summer of 2020, there was also significant opposition (Astor, 2020). . The current work seeks to contribute to existing social identity literature by examining how subtle racist rhetoric in the media, combined with a threat to the white American identity (prototypicality threat) may impact support for BLM. To address these hypotheses, white participants will be recruited …

Investigating Tribal Co-Management Of Caifornia’S Public Lands, Zachary Joseph Erickson

Cal Poly Humboldt theses and projects

Collaborative management with Indigenous groups is becoming increasingly common as many Indigenous communities continue to assert their inherent rights to self-determination. Due to the removal from and dispossession of lands, tribes often rely on access to public properties for various uses including ceremonies and gathering of culturally important plants. Some believe that the absence of indigenous involvement has also led to a decline in both the quality and abundance of culturally important resources, as well as limited the intergenerational transfer of traditional ecological knowledge, or TEK. There is increasing momentum toward re-engaging tribes as stewards of their ancestral lands through …

College Students' Autonomy, Self-Regulation, And Academic Self-Efficacy During Covid-19, Madelynne J. Avila

Cal Poly Humboldt theses and projects

The Coronavirus disease 2019 (COVID-19) forced college students to endure challenges that were unusual in the typical university environment. As self-determination theory, self-regulated learning theory, and social cognitive theory would suggest, college students’ need for satisfaction of autonomy and the ability to apply self-regulation may have been neglected due to COVID-related stressors (SDT; Ryan & Deci, 2000; SRLT; Zimmerman, 2012; SCT; Bandura, 2005). College students from a university (N = 94) participated in an online survey regarding their autonomy, self-regulated learning abilities, academic self-efficacy, and COVID-related stress. Using a moderated mediation model, the current study predicted that self-regulated learning …

Negative Social Media And Its Influence On Athlete's Performance, Bernd R. Huber

Cal Poly Humboldt theses and projects

This study aimed to investigate the potential impact of negative social media content on athletes' cortisol levels and subsequent performance. The study focused on the change in cortisol levels and differences in free throw performance, based on previous research findings. We hypothesized that negative social media postings would increase the stress experienced by student-athletes, resulting in elevated cortisol levels and decreased performance. Additionally, participants (n = 8) completed a questionnaire to examine the interaction between preexisting fear and the biological stress response. Contrary to expectations, there was no significant change in stress response, and negative postings did not have …

Examining Educator Burnout And Classroom Outcomes As Correlates To Teaching Pyramid Implementation, April N. Frazer

Cal Poly Humboldt theses and projects

The Teaching Pyramid is a research-based socio-emotional framework created for implementation in early childhood education programs. It is designed to support children’s socio-emotional development and decrease persistent challenging behaviors. Challenging child behaviors have been linked to early educator stress. Job stressors in early childhood educators have been previously linked to educator burnout.

This study examined fidelity of implementation of the Teaching Pyramid framework as well as experience being trained and coached on the framework in 21 early childhood educators. It evaluated how these variables correlated with educator burnout, children’s socio-emotional development, and observed quality of care in nine Head Start …

What Did Y’All Do?: Using Counter-Storytelling To Recall Student Affairs Professionals’ Response To Anti-Black Racist Incidents At One Predominantly White Institution In The Midwest, Darquillius J. Mayweather

Master's Theses and Doctoral Dissertations

This study paints a picture of student affairs professionals’ work after a string of anti-Black racist incidents at a predominantly White Midwestern university. In this study, student affairs professionals were asked to recount their responses to three anti-Black racist incidents at the university during the fall semester of 2016:
• September, 20, 2016, “KKK Leave N*****s” at Sing Hall;
• September 21, 2016, “Fuck U N*****s” at Mise Hall; and
• October 31, 2016, “leave n*****s” at Cord Hall.

This study used critical race theory (CRT) counter-storytelling methods to uncover frontline student affairs professionals’ responses to anti-Black racist incidents at …

Nourishing The Brain On Deep Space Missions: Nutritional Psychiatry In Promoting Resilience, Nihar N Pathare, Flavia Fayet-Moore, Jennifer A Fogarty, Felice N Jacka, Philip Strandwitz, Gary E Strangman, Dorit B Donoviel

Faculty, Staff and Students Publications

The grueling psychological demands of a journey into deep space coupled with ever-increasing distances away from home pose a unique problem: how can we best take advantage of the benefits of fresh foods in a place that has none? Here, we consider the biggest challenges associated with our current spaceflight food system, highlight the importance of supporting optimal brain health on missions into deep space, and discuss evidence about food components that impact brain health. We propose a future food system that leverages the gut microbiota that can be individually tailored to best support the brain and mental health of …

Postsurgical Morbidity And Mortality Favorably Informs Deep Brain Stimulation For New Indications Including Schizophrenia And Schizoaffective Disorder, Judith M Gault, Patrick Hosokawa, Daniel Kramer, Elyn R Saks, Paul S Appelbaum, John A Thompson, Ann Olincy, Nicola Cascella, Akira Sawa, Wayne Goodman, Nidal Moukaddam, Sameer A Sheth, William S Anderson, Rachel A Davis

Faculty, Staff and Students Publications

BACKGROUND: Deep brain stimulation (DBS) shows promise for new indications like treatment-refractory schizophrenia in early clinical trials. In the first DBS clinical trial for treatment refractory schizophrenia, despite promising results in treating psychosis, one of the eight subjects experienced both a symptomatic hemorrhage and an infection requiring device removal. Now, ethical concerns about higher surgical risk in schizophrenia/schizoaffective disorder (SZ/SAD) are impacting clinical trial progress. However, insufficient cases preclude conclusions regarding DBS risk in SZ/SAD. Therefore, we directly compare adverse surgical outcomes for all surgical procedures between SZ/SAD and Parkinson's disease (PD) cases to infer relative surgical risk relevant to …

Multiomics, Artificial Intelligence, And Precision Medicine In Perinatology, Mohan Pammi, Nima Aghaeepour, Josef Neu

Faculty, Staff and Students Publications

Technological advances in omics evaluation, bioinformatics, and artificial intelligence have made us rethink ways to improve patient outcomes. Collective quantification and characterization of biological data including genomics, epigenomics, metabolomics, and proteomics is now feasible at low cost with rapid turnover. Significant advances in the integration methods of these multiomics data sets by machine learning promise us a holistic view of disease pathogenesis and yield biomarkers for disease diagnosis and prognosis. Using machine learning tools and algorithms, it is possible to integrate multiomics data with clinical information to develop predictive models that identify risk before the condition is clinically apparent, thus …

Unmet Needs And Coping Strategies Of Older Underserved Veterans During The Covid-19 Pandemic, Trenton M Haltom, Joyce Tiong, Tracy L Evans, Nipa Kamdar, Gala True, Mark E Kunik

Faculty, Staff and Students Publications

INTRODUCTION: The COVID-19 pandemic has had profound impacts on people with diabetes, a group with high morbidity and mortality. Factors like race, age, income, Veteran-status, and limited or interrupted resources early in the COVID-19 pandemic compounded risks for negative health outcomes. Our objective was to characterize the experiences and needs of under-resourced Veterans with type 2 diabetes during the COVID-19 pandemic.

METHODS: We conducted semi-structured qualitative interviews (March through September 2021) with U.S. military Veterans with diabetes. Transcripts were analyzed using a team-based, iterative process of summarizing and coding to identify key themes. Participants included Veterans (n = 25) who …