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Spartan Daily, September 10, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 8

Sjsu Erfa Board Minutes, May 5, 2025, San Jose State University, Emeritus And Retired Faculty Association

SJSU ERFA Minutes

SJSU ERFA Executive Board Minutes

May 5, 2025

Spartan Daily, September 9, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 7

Climate Change-Related Threats To Railroads: Implications For Threat, Hazard And Risk Assessment, Frances L. Edwards, Daniel C. Goodrich

Faculty Research, Scholarly, and Creative Activity

Climate change has created new challenges for railroads around the world. The rail systems operate in open environments, subjecting them to increased heat, changing locations of heavy rains, developing sea level rise and storm surge, and a longer and stronger wildfire season. This research investigates how an updated threat and hazard identification and risk assessment (THIRA) can lead to the development of climate adaptation strategies that limit damage and disruption to the railroad enterprise. The THIRA analyzes which threats are of most concern in a specific rail segment, and which climate change adaptation strategies give a beneficial return on investment.

Spartan Daily, September 4, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 6

Prevalence Of Exposures And Moral Injury In First Responders, Shira Maguen, Soma De Bourbon, Adam Batten, Michael Mason, April Sloan, Daniel Nazzareta, Joseph Graterol, Simon Pang, Miranda Worthen

Faculty Research, Scholarly, and Creative Activity

Objectives: Workers in high-stakes occupations, such as first responders, are at risk of exposure to potentially morally injurious events (PMIEs) and moral injury, yet research with first responders has been scarce. This study aimed to assess the frequency of exposure to PMIEs, the prevalence of moral injury, and the correlation between moral injury and other mental health symptoms. Methods: In this cross-sectional study, firefighters, emergency medical technicians (EMTs), and paramedics working for a large urban Fire Department in California were invited to complete an online, confidential survey using validated scales to assess exposure to PMIEs, moral injury symptoms, and symptoms …

Spartan Daily, September 3, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 5

Acoustic Wave Manipulation Through Sparse Robotic Actuation, Tristan Shah, Noam Smilovich, Feruza Amirkulova, Samer Gerges, Stas Tiomkin

Faculty Research, Scholarly, and Creative Activity

Recent advancements in robotics, control, and machine learning have facilitated progress in the challenging area of object manipulation. These advancements include, among others, the use of deep neural networks to represent dynamics that are partially observed by robot sensors, as well as effective control using sparse control signals. In this work, we explore a more general problem: the manipulation of acoustic waves, which are partially observed by a robot capable of influencing the waves through spatially sparse actuators. This problem holds great potential for the design of new artificial materials, ultrasonic cutting tools, energy harvesting, and other applications. We develop …

Human Factors For A Better World: Case Studies In Community Ergonomics, Hanna J. Barton, Andrew Thactcher, Maurita T. Harris, Wendy A. Rogers, Dan Nathan-Roberts, Leah Newman, Carlo Caponecchia

Faculty Research, Scholarly, and Creative Activity

This panel brings together global experts to explore the evolving practice of community ergonomics—an approach that applies Human Factors and Ergonomics (HFE) to co-design systems with and for marginalized communities. Building on the lessons articulated in Barton et al. (2025), panelists will present diverse case studies that highlight both the promise and complexity of community-engaged HFE work. Panelists will reflect on the epistemological shifts, methodological adaptations, and relational commitments required to move toward genuine collaboration and social impact. Attendees will leave with tangible strategies for engaging communities as co-designers, as well as deeper insight into how our assumptions as HFE …

Directional Vibrotactile Takeover Requests On A Wrist-Worn Device: Effects Of Age, Pattern Type, And Urgency In Automated Driving, Wei Hsiang Lo, Gaojian Huang

Faculty Research, Scholarly, and Creative Activity

Drivers are still required to perform the takeover task in highly automated vehicles. This task, which is cognitively and physically demanding, may present challenges for older adults due to general age-related declines in perception and cognition. Tactile modalities that may not be occupied by many non-driving-related tasks could serve as a potential solution for delivering takeover requests. Among these, directional vibrotactile stimuli presented via a wrist-worn device represent a promising approach. However, the effects of the two common types of directional vibrotactile patterns, dynamic patterns that vibrate sequentially at different locations and static patterns that vibrate at fixed locations, are …

The Association Between Cardiac Vagal Activity And Urinary Catecholamine: Investigating The Effect Of Race And Sex, Li Shen Chong, Betty Lin, Elana B. Gordis, De Wayne P. Williams, Julian F. Thayer

Faculty Research, Scholarly, and Creative Activity

Black individuals are at greater risk for the development of cardiovascular diseases compared to White individuals. Autonomic nervous system (ANS) dysregulation has been identified as a significant risk factor contributing to racial disparities in cardiovascular disease, yet systematic racial differences that affect the measurement of ANS activity among White and Black participants are likely obscuring understanding about ANS-health disparity links. Moreover, sex differences in ANS activity have been observed. Thus, efforts to elucidate the comparability of ANS indices across race and sex are needed. This study aimed to investigate the effects of race and sex on the associations between two …

Exploring The Use And Misuse Of Large Language Models, Hezekiah Paul D. Valdez, Faranak Abri, Jade Webb, Thomas H. Austin

Faculty Research, Scholarly, and Creative Activity

Language modeling has evolved from simple rule-based systems into complex assistants capable of tackling a multitude of tasks. State-of-the-art large language models (LLMs) are capable of scoring highly on proficiency benchmarks, and as a result have been deployed across industries to increase productivity and convenience. However, the prolific nature of such tools has provided threat actors with the ability to leverage them for attack development. Our paper describes the current state of LLMs, their availability, and their role in benevolent and malicious applications. In addition, we propose how an LLM can be combined with text-to-speech (TTS) voice cloning to create …

Deep Learning-Based Drowsiness Detection System For Driver’S Safety, Sindhu Vidyanathan Dixith, Shrikant Jadhav, Youngsoo Kim, Naveenkumar Jayakumar

Faculty Research, Scholarly, and Creative Activity

Driver drowsiness is a leading contributor to road accidents, accounting for over 100,000 crashes and approximately ~1000 fatalities each year in the United States alone, as per National Safety Council (NSC). To mitigate this urgent public-safety risk, we propose a real-time Driver Drowsiness Detection System that achieves both high accuracy and fast inference on standard hardware. Our key idea is to combine two complementary deep-learning strategies: 1) a custom Convolutional Neural Network (CNN) paired with a Support Vector Machine (SVM) classifier, and 2) a lightweight transfer-learning model built upon a pre-trained convolutional backbone. We evaluate these approaches on two datasets: …

Using Large Language Models To Investigate The Origin Of Chronic Wasting Disease, G. Kent Webb

Faculty Research, Scholarly, and Creative Activity

This use case reports on the impressive output, hallucinations, instability, and limitations of three Large Language Models (LLMs): ChatGPT, Gemini, and Grok. The LLMs were prompted in an investigative sequence and responses checked. The collected information supports the common theory that chronic wasting disease (CWD) in North America originated in 1967 at a research facility in Fort Collins, Colorado, where deer were reported to have been exposed to sheep with a similar disease - scrapie. Findings include that: no sheep with scrapie were detected in the area around Fort Collins prior to 1967; domestic sheep reportedly exposed to scrapie were …

A Context-Sensitive Roadway Classification Framework For Speed Limit Setting In The Us, Cheng Kai Hsu, Melody Tsao, Marcel E. Moran, Julia B. Griswold, Robert J. Schneider, John M. Bigham

Faculty Research, Scholarly, and Creative Activity

In the US, speed limit setting (SLS) procedures have historically relied on driver-behavior-based methods, such as the 85th percentile speed, which are considered objective and allow for consistent application. However, this approach has notable shortcomings, including drivers’ tendency to underestimate their speeds, speed creep, and insufficient consideration of vulnerable road users, which may conflict with the Safe System Approach and Vision Zero initiatives endorsed by the USDOT (US Department of Transportation). In contrast, context-sensitive approaches, which classify roads based on roadway typologies, have been developed in countries like New Zealand, Sweden, the Netherlands, and Australia. While effective, these approaches have …

Unveiling The Veil: Understanding The Intersection Of Racism And Body Image Among Vietnamese American Young Adults, Thien Dang, Meekyung Han

Faculty Research, Scholarly, and Creative Activity

Asian Americans have experienced persistent gendered racism, racial microaggressions, and orientalism. These factors have contributed to dissatisfaction with their body image and have led some individuals to turn to body modification in order to cope with psychological distress and conform to White beauty standards. However, limited research has explored how Vietnamese Americans—one of the fastest-growing Asian American populations—experience and navigate racial dynamics related to body image, particularly in relation to gender differences and the role of cultural identity. To address this knowledge gap, a qualitative study was conducted to explore the intersection of racism, internalized racism, and body image dissatisfaction, …

Aurora 2.0: A Fluorogenic Dye Library For Expanding The Capability Of Protein-Adaptive Differential Scanning Fluorimetry (Padsf), Annemarie F. Charvat, Kayleigh Mason-Chalmers, Aneta Grabinska-Rogala, Shloka Shivakumar, Zachary Gale-Day, Taiasean Wu, Zoe Millbern, Jonathan B. Grimm, Emma C. Carroll, K․ Peter R․ Nilsson, Luke D. Lavis, Nelson R. Vinueza, Jason E. Gestwicki

Faculty Research, Scholarly, and Creative Activity

Differential Scanning Fluorimetry (DSF) is a biophysical assay that is used to estimate protein stability in vitro. In a DSF experiment, the increased fluorescence of a solvatochromatic dye, such as Sypro Orange, is used to detect the unfolding of a protein during heating. However, Sypro Orange is only compatible with a minority of proteins (< 30 %), limiting the scope of this method. We recently reported that protein-adaptive DSF (paDSF) can partially solve this problem, wherein the protein is initially pre-screened against ∼300 chemically diverse dyes, termed the Aurora collection. While this approach significantly improves the number of targets amenable to DSF, it still fails to produce protein-dye pairs for some proteins. Here, we report the expansion of the dye collection to Aurora 2.0, which includes a total of 517 structurally diverse molecules and multiple new chemotypes. To assess performance, these dyes were screened against a panel of ∼100 proteins, which were selected, in part, to represent the most challenging targets (e.g. small size). From this effort, Aurora 2.0 achieved an impressive success rate of 94 %, including producing dyes for some targets that were not matched in the original collection. These findings support the idea that larger, more chemically diverse libraries improve the likelihood of detecting melting transitions across a wider range of proteins. We propose that Aurora 2.0 makes paDSF an increasingly powerful method for studying protein stability, ligand binding and other biophysical properties in high throughput.

Decadal Change In Deep-Ocean Dissolved Oxygen In The North Atlantic Ocean And North Pacific Ocean, Henry A. Ruhl, Christine L. Huffard, Monique Messié, Thomas P. Connolly, Thomas Soltwedel, Frank Wenzhöfer, Rodney J. Johnson, Nicholas R. Bates, Susan Hartman, Anita Flohr, Edward W. Mawji, David M. Karl, James Potemra, Fernando Santiago-Mandujano, Tetjana Ross, Kenneth L. Smith

Faculty Research, Scholarly, and Creative Activity

Declining dissolved oxygen concentrations are documented at upper and mid ocean depths, but less is known about the deep ocean. Long time-series measurements of dissolved oxygen analyzed with Winkler titration over several decades reveal regional differences at six stations in the abyssal North Atlantic Ocean and North Pacific Ocean. A significant decline in dissolved oxygen was evident at two stations in the northeast Pacific Ocean at 4000–4200 m depth (Stations PAPA and M). A similar decreasing but insignificant trend was recorded in the Arctic region of the North Atlantic Ocean (HAUSGARTEN). However, there was no significant decrease in dissolved oxygen …

Covid-19 Prevention Behaviors Are Congruent Within Social Networks Of Disenfranchised Hispanic And Criminal Legal Involved Community Members, Victoria Umutoni, Khavita Bhavan, Nickolas Zaller, Amelia Knopf, Moctezuma Garcia, Russell A. Brewer, Makenna Meyer, Faye Taxman, O’Dell Johnson, Matthew Aalsma, John Schneider

Faculty Research, Scholarly, and Creative Activity

The COVID-19 (COVID) pandemic has had a disproportionate impact on people who have low income and identify as Hispanic or Latinx (PLIH) as well as those with criminal Legal Involvement (CLI). These two groups, and their intersection, are often disenfranchised from livable wage employment, basic social services, and healthcare, which are vital to prevent the spread of COVID. We examined baseline data from the Community Network-Driven COVID Testing of Marginalized Population in the Central US (C3) which included 1036 participants: 32.1% PLIH, 39.6% CLI, 10.6% who identified as both PLIH and CLI, and 17.6% who were neither PLIH nor CLI. …

Spartan Daily, August 28, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 4

Accelerating The Fusion Workforce In The Usa, Carlos Paz-Soldan, Eva Belonohy, Troy Carter, Laleh E. Coté, Evdokiya Kostadinova, Calvin Lowe, Subash L. Sharma, Sybil De Clark, Jaydeep Deshpande, Kate Kelly, Bobbi Makani, David A. Schaffner, Kathreen E. Thome

Faculty Research, Scholarly, and Creative Activity

The fusion energy research and development landscape has seen significant advances in recent years, with important scientific and technological breakthroughs and a rapid rise of investment in the private sector. The workforce needs of the nascent fusion industry are growing at a rate that academic workforce development programs are not currently able to match. This paper presents the findings of the Workforce Accelerator for Fusion Energy Development Conference held in Hampton, Virginia, United States of America (USA), on 29-30 May 2024, which was funded by the National Science Foundation of the USA. A major goal of the conference was to …

Poster: Threat Intelligence & Modeling Practices For Iomt Devices Using Wi-Fi Communications, Eva Wilson, Cody Ourique, Bernardo Flores

Faculty Research, Scholarly, and Creative Activity

The integration of internet connectivity into medical devices, known as the Internet of Medical Things (IoMT), is revolutionizing modern healthcare through remote monitoring and advanced diagnostics. Among these devices, the Continuous Positive Airway Pressure (CPAP) machine plays a critical role in managing patients with Sleep Apnea. However, the security of CPAP devices presents significant concerns due to potential vulnerabilities that could lead to critical failures, such as device shutdowns. An analysis was made of the device's connectivity interface, to identify potential exploit points and vulnerabilities. Additionally, we evaluated whether existing threat modeling frameworks - namely the MITRE Adversarial Tactics, Techniques, …

Synthetic Malware Image Generation Based On Generative Models Against Zero-Day Attacks, Arjun Sudheer, Ayesha Ahmed, Fabio Di Troia, Younghee Park

Faculty Research, Scholarly, and Creative Activity

Malware detection is a critical task for protecting our assets from attacks. However, traditional approaches to malware detection often struggle with limited datasets, which hinder the effectiveness of machine learning models. In this paper, we propose a malware image generation system designed to craft high-quality synthetic malware image samples, addressing the challenges posed by small datasets in malware detection. The proposed system utilizes two popular generative models, WGAN-GP and Diffusion, to generate synthetic malware images. It converts malware binary files into image files using four different color spaces: monochrome, grayscale, RGB, and CMYK. These images are then evaluated based on …

Context-Aware Natural Language Processing For Malware Detection, Helen Liu, Summer Mccune, Quang Duy Tran, Fabio Di Troia, Younghee Park

Faculty Research, Scholarly, and Creative Activity

As malware continues to evolve and cyber attacks become increasingly prevalent, it is critical to develop effective malware classification techniques for the detection and prevention of such malicious attacks. In our research, we approach malware classification from a natural language processing perspective to explore how various tokenization techniques on malware opcode features can enhance classification accuracy and combat malware obfuscation and evolution techniques with a deep learning approach, previously unaddressed by existing research. We bridge this gap by conducting extensive hyperparameter tuning experiments that examine the effects of five common tokenization methods, that is, White Space Separation, Top Single Words, …

Spartan Daily, August 27, 2025, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2025

Volume 165, Issue 3

Poster: Development Of Situation Awareness Measurement For Cybersecurity Professionals, David Schuster, Crystal Fausett, Maiyi Huang, Sabina M. Patel, Jenna Korentsides, Joseph R. Keebler, Elizabeth H. Lazzara

Faculty Research, Scholarly, and Creative Activity

Better understanding of the implications of many aspects of human behavior, especially that of cybersecurity professionals, can help develop the cybersecurity workforce. Despite efforts aimed at documenting and understanding cybersecurity professionals' knowledge, understanding of how cognition supports human performance in specific cybersecurity tasks remains limited. Specifically, understanding of the elements of situation awareness (SA), defined as goal-directed knowledge, is necessary to support human-centered evaluation, selection, training, and recruitment strategies. In this poster, we propose a framework for developing measures of situation awareness for cybersecurity professionals and a method of capturing initial effectiveness data that does not rely on access to …

Poster: Cloudsweeper: Leveraging Large Language Models To Personalize Sensitive Archive Search, Victor Escuerdo, Sergio Talavera, Gautam Santhanu Thampy, Ivan Torres, Daniel Vega Lojo, Chris Kanich, Magdalini Eirinaki

Faculty Research, Scholarly, and Creative Activity

As cyber threats continue to evolve, overlooked or neglected files stored in cloud services can pose significant risks to personal privacy and data security. In this paper we present Cloudsweeper, a system that aims to improve cloud storage security by creating tools that help users identify and manage sensitive or unwanted files. Cloudsweeper leverages Large Language Models (LLMs) with a Retrieval-Augmented Generation (RAG) architecture to develop a personalized and privacy-focused archive search system. Cloudsweeper represents an innovative approach to secure archive management, balancing user control and privacy in cloud storage environments.

Testimonios: The Experiences Of An Undocumented Student In California Post-Daca Rescindment, Isabel Rangel

McNair Research Journal SJSU

After Deferred Action for Childhood Arrival (DACA, 2012) was rescinded

by the Trump Administration in 2017, many students were left in “limbo

legality” (Gonzalez 2012) This study addresses the question, “What are the

experiences of undocumented students regarding their academic motivation

toward graduation now that DACA has been rescinded at San Jos. State

University (SJSU)?” Grounded in a Chicana Feminist Epistemology

approach, the methodology of testimonio is used to capture the experiences

of the author alongside an undocumented graduate student. Findings

suggest that college campuses should incorporate faculty knowledgeable in

policies that affect undocumented students, Undocumented Ally trainings

in college …

Understanding Child Noncompliance In The Early Care Setting, Melody Mann

McNair Research Journal SJSU

This study examines how teachers respond to children’s noncompliance in

early care settings. This structured observational study will focus on the

moment-to-moment interactions occurring within the preschool classroom

between both the child and teacher. It is predicted that (1) teacher’s direct

bids to children will promote greater instances of child compliance than

indirect bids, and (2) teachers’ responsive language will promote greater

instances of child compliance than restrictive language. The results of this

study will contribute to existing knowledge about the nature of teacher

child interactions in the early care settings.

Increasing And Improving Diversity And Hiring Of Individuals With Disabilities In The Workplace, Joshua Zhang

McNair Research Journal SJSU

This paper is a literature review of several literature on disability, diversity,

human resource/human resource management, and hiring in the

workplace/organization. The research question is how can employers

improve and increase hiring of individuals with disabilities in their

organizations? The objectives of this literature review paper are 1. Research

and analyze existing literature on disability, diversity, and workplace hiring,

2. Identify any limitations in gaps in research literature, and 3. Propose and

suggest areas and topics for future research. Each of the academic sources

in this paper are presented and discussed along with analysis. Additionally,

recommendations on how to best …