Digital Commons Network^™

An Assessment Of The Viva Callesj September 2025 Event In San José, Richard Kos, Adam Cohen

Mineta Transportation Institute

Viva CalleSJ is an open-streets initiative where several miles of the City of San José’s streets are closed to vehicular traffic, allowing residents to walk, bike, scooter, and skate freely. This report evaluates the Viva CalleSJ event held in San José on September 7, 2025, which attracted more than 150,000 participants. Using a mixed-methods approach, this evaluation examines aspects such as attendance, activities, modal access, and economic impacts, utilizing data from participant surveys (in English, Spanish, and Vietnamese), interviews, and observational analysis. The findings indicate that the Viva CalleSJ September 2025 event was largely successful in achieving its objectives, including …

What Do Americans Think About Federal Tax Options To Support Transportation? Results From Year Sixteen Of A National Survey, Asha Weinstein Agrawal, Hilary Nixon

Mineta Transportation Institute

This report summarizes the results from the sixteenth year of a national public opinion survey asking U.S. adults questions related to their views on federal transportation taxes. A nationally representative sample of 2,539 respondents completed the online survey from February 3 to February 27, 2025. The questions test public opinions about raising the federal gas tax rate, replacing the federal gas tax with a new mileage fee, and imposing a mileage fee just on commercial travel. In addition to asking directly about support for these tax options, the survey collected data on respondents’ views on the quality of their local …

Topographic And Upwelling Effects On Surface Lagrangian Coherent Structures Of Cape Mendocino, Basil Martin Darby

Master's Theses

The goal of this study is to investigate fine-scale Lagrangian coherent structure (LCS) generation in a coastal upwelling setting with prominent topography using a high-resolution global-ocean circulation model (LLC4320). I examine LCS properties, spatiotemporal evolution and vertical structure, as well as possible connections to submesoscale variability and chlorophyll. The LLC4320 simulation in the Cape Mendocino region is evaluated using high-resolution satellite and other ocean observations. Additionally, this study uses a novel dynamical systems technique by relating the LCS of flow fields to the physical dynamics of the mesoscale-to-submesesoscale transition. It is found that time series of short timescale LCS yield …

Homelessness Following Jail Exit Among Previously Housed Individuals, Emily E. Ager, Meghan M. Hewlett, Dallas Augustine, Eve Perry, Hemal K. Kanzaria, Kenneth Perez, Jacob Izenberg, Maria C. Raven

Faculty Research, Scholarly, and Creative Activity

Incarceration is a recognized risk factor for homelessness. However, most research focuses on the relationship between homelessness and prison incarceration. Jail incarceration is more common compared to prison incarceration, but little data exists on its impact on housing. The objective of this study is to examine the occurrence of housing loss after jail incarceration among individuals without prior evidence of homelessness and the associated risk of reincarceration. In this retrospective cross-sectional study, we identified adults without evidence of homelessness who became unhoused within 6 months of jail incarceration. We compare pre-incarceration emergent and urgent health and social services utilization among …

Retrieval Augmented Framework For Deepfake Audio Detection, Avinash Saxena

Master's Theses

The widespread use of AI-based audio deepfakes threatens severely to undermine media integrity and public trust. Speech synthesis techniques have improved dramatically in voice conversion (VC) and text-to-speech (TTS) in recent years, making forgeries sound highly realistic, and concerns are raised about possible malevolent uses. Existing state-of-the-art techniques for identifying fake speech have proven to be effective in some cases but are still limited in application and robustness when faced with novel attacking strategies, different acoustic conditions, or alternative linguistic domains. To address some of these limitations, the current research presents a novel deepfake audio detection system based on personalized …

Digital Neuropsychology And Social Anxiety: The Effect Of Observer Presence And Personality On Stress And Cognition, Ava M. Dixon

Master's Theses

This study examined how observer presence and social anxiety influence stress and cognitive performance during neuropsychological assessments, focusing on the potential benefits of unsupervised digital testing environments. Eighty university students were randomly assigned to observed or unobserved digital neuropsychological conditions and completed assessments of social cognition and executive functioning and questionnaires of social anxiety and personality. Participants also completed measures of state anxiety and heart rate variability at baseline and after cognitive tests. The findings indicated that observation led to higher subjective anxiety, but it did not produce significant interactions with social anxiety on stress or cognitive performance. Post-hoc analyses …

Reclaiming Relational Pedagogies: The Role Of Talking Circles In Decolonizing Higher Education Classrooms, Veneice Lacy

Faculty Research, Scholarly, and Creative Activity

This article explores the use of Talking Circles as a decolonizing pedagogical practice within higher education, grounded in Indigenous epistemologies and relational worldviews. Drawing on the works of Indigenous scholars such as Graveline, Wilson, Archibald, and Simpson, the article positions Talking Circles not merely as instructional strategies but as ceremonial, spirit-centered pedagogies that resist the Eurocentric hierarchical and individualistic norms of Western academia. Through autoethnographic reflection and student narratives from undergraduate and graduate education courses, the article demonstrates how Talking Circles foster relational accountability, ethical engagement, and transformative learning. By centering oral tradition, reciprocity, and communal learning, Talking Circles reconfigure …

The Double-Edged Sword: Polarized Stakeholder Engagement With Corporate Sociopolitical Activism And Its Downstream Effects On Brand Performance, Mithila Guha, Daniel Korschun, Trina Larsen Andras

Faculty Research, Scholarly, and Creative Activity

This study explores how stakeholder reactions to corporate sociopolitical activism (CSA) on ‘X’ influence brand engagement and stock performance. Our research shifts focus from corporate messaging to stakeholder-driven conversations, demonstrating that CSA’s impact extends beyond brand statements and is shaped by public discourse. We analyze both direct replies to brand-authored CSA posts and organic user-initiated discussions, where consumers engage brands using hashtags and mentions. Using data from the 2022 humanitarian crisis in Ukraine, we examine 41,358 targeted user posts referencing 159 publicly traded brands’ CSA engagement. Sentiment analysis and topic modeling of 1,322 brand tweets, 39,578 replies, and stock data …

“It Haunts Me Still”: Exposure To Potentially Morally Injurious Events In First Responders, Miranda Worthen, Shira Maguen, Soma De Bourbon

Faculty Research, Scholarly, and Creative Activity

Moral injury is a biopsychosocial, behavioral, and spiritual consequence that may occur for individuals in high-risk occupations after acting, failing to prevent, or witnessing events that go against their deeply held morals or values. While there has been extensive research on the types of events that may lead to moral injury for veterans, and a growing literature on healthcare workers, limited research has explored the experiences of first responders. This study builds on a multi-year participatory action research study with a large fire department in northern California aimed at understanding and mitigating moral injury among first responders. The present article …

Towards A Generalized And Optimized Apriori Approach, Artem Abdikov

Master's Theses

Apriori is a machine learning algorithm developed in 1994 by R. Agrawal and R. Srikant for association rule mining purposes. This family of algorithms takes transactional data and analyzes relationships between variables in large datasets. The typical output of such algorithms is a prediction that if users choose item X, it is highly likely that they will also choose item Y. Apriori is known to be a robust algorithm and is used by many large companies in order to analyze user tendencies and even make recommendations. Although Apriori is a powerful algorithm, its original implementation is known to have limitations, …

Spartan Daily, November 25, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 39

“What Are We And What’S Coming Next?”: Queer People’S Experiences During Sociopolitical Unrest In The Us, Ariana Cristal Morales

Master's Theses

Queer (lesbian, gay, bisexual, transgender, queer, or other gender and sexual identities) folx have become a major focal point during political elections. As political climates have projected forced attacks towards queer populations, society has followed suit. Investigation on the impacts of such changes towards queer folx is important to uncover, as sociopolitical climates have shifted within the last 10 years in the US. The present study utilizes a phenomenological framework to understand the lived experiences of queer participants living in the US from 2015-2025 during political and social shifts. Semi-structured interviews were utilized to explore 10 queer participant’s lived experience …

A Triple Bottom Line Analysis Of Food Waste-To-Bioenergy At California University Campuses: Social Enablers Break Down Economic Barriers, Anjali Sharma

Master's Theses

Greenhouse gas emissions from food waste (FW) and energy generation are two major hurdles to the climate crisis. Previous research shows that waste-to-energy systems may provide a solution to both these challenges, particularly at university campuses, due to their high FW generation and high energy needs. Despite this, few academic institutions in California, US, have adopted waste-to-energy systems, and campus-specific challenges and opportunities associated with these systems remain underexplored. For this study, I use an Environmental, Economic, and Social (EES) lens to document the current landscape of FW management and implementation of food waste-to-bioenergy at campuses in each of the …

The Initial User Experience Of A Gamified Mental Health App, Angill Lynae Oliva

Master's Theses

Despite the availability of mobile mental health apps, high dropout rates due to low user engagement and attitudes about their effectiveness remain significant challenges. The present study examined the relationship between digital therapeutic alliance (i.e., the efficacy of therapeutic quality for digitalized mental health interventions) and college students’ engagement and perceptions of use with a gamified mental health app, SuperBetter. Digital therapeutic alliance was measured using the Working Alliance Inventory-Short Revised (WAI-SR), while engagement was assessed by the total number of completed activities in the SuperBetter app. Students’ intrinsic motivation was measured using the Intrinsic Motivation Inventory (IMI); and perceptions …

Spartan Daily, November 20, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 38

An Exploration Of Image Segmentation Techniques For Real-Time Product Detection, Andrew C. Dunton

Master's Theses

Recent progress in LLMs enables advanced multimodal understanding, but their high computational cost necessitates monetization strategies like interactive advertising. While bounding boxes show promise for this concept, they can lack precision and visual appeal. Image segmentation offers a superior solution but faces a dual problem: traditional models demand scarce, costly training data, and open-vocabulary segmentation models like SAM are class-agnostic, unable to semantically identify a "consumer product" object class. In this research, we address these limitations by: 1) developing the Prompt-Guided Inpainting Framework (PGIF), which injects negative prompts to generate robustly annotated synthetic segmented product images; 2) investigating the Class-Agnostic …

Spartan Daily, November 19, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 37

Spartan Daily, November 18, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 36

Building Consensus For School Librarian Collaboration: A Delphi Study, Pamela C. Harland, Susan D. Ballard, Rachel V. Small

Learning Hub

This Delphi study engaged 38 national experts in school librarianship to develop a consensus-based model of school librarian collaboration (SLC) that reflects current practice. Through three iterative rounds the panel achieved strong consensus on a definition of SLC, a framework representing a continuum of collaborative practice, and necessary conditions for success. The resulting definition of SLC is "an educator-to-educator partnership to enhance student learning through complementary expertise that develops over time and is built on mutual trust, shared goals, and open communication." The seven levels continuum of SLC are: Autonomy, Curation, Contribution, Coordination, Integration, Partnership, and Assurance. These levels allow …

Radiation Hardness Study Of Finfet And Gate-All-Around Fet Sram, Albert Lu

Master's Theses

Radiation, such as alpha particles or neutrons, is hard to control and can come from sources such as trace impurities or cosmic rays from space. These can then strike a semiconductor device, such as a Static Random Access Memory (SRAM) cell, and cause the SRAM to have its bit flipped. This bit flip is often just a temporary effect and is thus called a single event upset (SEU). Although it is temporary, a bit flip can cause severe consequences, such as affecting program functionality by causing incorrect data to be used. This is made worse in critical environments that need …

Climatology Of Northeast Winds In Northern And Central California: A New Characterization Of The Diablo Wind, Alana R. Macken

Master's Theses

Diablo winds in northern California are known for driving some of the most destructive wildfires in state history. The Camp Fire of 2018, which caused at least 85 civilian fatalities, is just one example of the devastating outcomes associated with these rapidly developing downslope windstorms. While they are known to occur most frequently from fall through spring, much about the structure, evolution, and full spatial extent of these events remains poorly understood. Most previous studies have focused on a limited number of high-impact cases or have defined events using humidity-based thresholds in isolated regions such as the North Bay. As …

Early Visual Predictors Of Progression To Alzheimer’S Disease And Dementia With Lewy Bodies, Abril Baez

Master's Theses

We examined whether specific visual cognitive skills predict progression from Mild Cognitive Impairment (MCI) to Alzheimer’s disease (AD), or dementia with Lewy bodies (DLB). The Benson Complex Figure Task (BCFT) was used to measure visual perception and construction (copy), and visual memory (recall). National Alzheimer Coordination Center longitudinal dataset included participants who remained stable (MCI-stable; n =2630), progressed to AD (MCI-AD; n =798), or progressed to DLB (MCI-DLB; n =59). Baseline BCFT scores were entered into logistic regression models predicting diagnostic outcome. Impaired copy performance was significantly associated with MCI-DLB (B = 0.79, OR = 2.21, BCa CI [0.26, 1.36], …

Forecasting Pediatric Emergency Department Arrivals: Evaluating The Role Of Exogenous Variables Using Deep Learning Models, Egbe Etu Etu, Jordan Larot, Kindness Etu, Joshua Emakhu, Sara Masoud, Imokhai Tenebe, Gaojian Huang, Satheesh Gunaga, Joseph Miller

Faculty Research, Scholarly, and Creative Activity

Background Forecasting pediatric emergency department (ED) demand remains a critical challenge in healthcare operations. This study aimed to identify exogenous variables influencing pediatric ED visits and evaluate the performance of different forecasting models. Method Using a retrospective observational design, we analyzed 192,347 pediatric ED visits across nine hospitals in Southeast Michigan between 2017 and 2019. Patient data were aggregated into daily arrival counts and enriched with exogenous variables such as weather, air quality, pollen, calendar, Google search trends, and chief complaints. Feature selection was performed using XGBoost and SHapley Additive exPlanations to identify the most influential predictors. Three forecasting models …

Sjsu Erfa Board Minutes, October 3, 2025, San Jose State University, Emeritus And Retired Faculty Association

SJSU ERFA Minutes

SJSU ERFA Executive Board Minutes

October 3, 2025

Sjsu Erfa Board Minutes, September 8, 2025, San Jose State University, Emeritus And Retired Faculty Association

SJSU ERFA Minutes

SJSU ERFA Executive Board Minutes

September 8, 2025

Spartan Daily, November 13, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 35

Spartan Daily, November 11, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 34

Spartan Daily, November 6, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 33

Embedding-Driven Synthetic Malware Generation With Autoencoders And Cluster-Tangent Diffusion, Gunnika Kapoor, Sathvika Nadipalli, Fabio Di Troia

Faculty Research, Scholarly, and Creative Activity

Malware has become increasingly sophisticated over the years, with zero-day attacks emerging at an alarming pace. Effective detection and analysis demand real malware samples, which are expensive and skill-dependent to extract. As a result, generating high quality synthetic samples from scarce data sets becomes a crucial method for strengthening detection software. This paper focuses on presenting generation techniques that optimize the embedding space to produce high-quality synthetic samples, even under constrained datasets. The dataset used in this paper consists of 500 Windows malware API call samples that were processed using embedding and Generative AI (Gen AI) techniques to generate synthetic …

Spartan Daily, November 5, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 32