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Conniff, Michael L. (1942-2025), San Jose State University

Emeritus and Retired Faculty Biographies

University of California, 1968, BA, Latin American Studies

Stanford University, 1969, MA, Latin American Studies

Stanford University, 1976, Ph.D., History

Affective Polarization In Latin America, Juan A. Moraes, Sergio Béjar

Faculty Research, Scholarly, and Creative Activity

Studies on the determinants and consequences of affective polarization have proliferated in the past decade, focusing mostly on the US and Western European countries. Empirical and anecdotal evidence presented in this chapter, however, suggests that such a phenomenon is also prevalent in many Latin American countries, which may have important consequences for the stability and survival of democracy in a region where partisan institutions tend to be weak. In this chapter, we present a critical review of the scant literature on affective polarization in Latin America. We then carefully analyze levels of partisan affective polarization (PAP) and leader affective polarization …

Sjsu Erfa News, Summer 2025, San Jose State University, Emeritus And Retired Faculty Association

Emeritus and Retired Faculty Association (ERFA) Newsletter

Volume 38, No 4

Quantifying Marine Carbon Dioxide Removal Via Alkalinity Enhancement Across Circulation Regimes Using Ecco-Darwin And 1d Models, Kay Suselj, Dustin Carroll, Daniel Whitt, Bridget Samuels, Dimitris Menemenlis, Hong Zhang, Nate Beatty, Anna Savage

Faculty Research, Scholarly, and Creative Activity

Ocean Alkalinity Enhancement (OAE) is emerging as a viable method for removing anthropogenic (Formula presented.) emissions from the atmosphere to mitigate climate change. To achieve substantial carbon reductions, OAE would need to be deployed at scale across the global ocean. Hence, there is a need to quantify how the efficiency of OAE varies globally across a range of space-time scales in preparation for field deployments. Here we develop a marine carbon dioxide removal (mCDR) efficiency evaluation framework based on the data-assimilative ECCO-Darwin ocean biogeochemistry model, which separates and quantifies two key factors over seasonal to multi-annual timescales: (a) mCDR potential, …

An Ambient Nox Reduction Reactor System With And Without Forced Air, Hamid Rahai, Rylan Moffit, Komal Gada, Jeremy Bonifacio

Mineta Transportation Institute

Ambient nitrogen oxide (NOX) is one of the main ingredients involved in the formation of ground-level ozone (smog), which contributes to global warming and the formation of particulates in the atmosphere and causes respiratory illnesses, especially in children, older adults, and people with lung diseases. Investigations on adding titanium dioxide (TiO2) nanoparticles to the paint used on concrete surfaces such as buildings and its potential in reducing ambient NOX concentration have provided opportunities for the research and development of methods for passive control and filtration of the ambient NOX. The present research used numerical geometrical optimization to identify an optimized …

Hydrogen Fuel Cell Application For Port Drayage Truck: Integrated Transportation And Energy Modeling, Shams Tanvir, Emu Ghosh

Mineta Transportation Institute

This report investigates the viability of hydrogen Fuel Cell Electric Vehicles (FCEVs) for port drayage applications, focusing on both energy modeling and economic feasibility. Port drayage—trucking operations that move goods a short distance to and from ports—is a key part of freight logistics and the critical movement of goods in American communities. This project developed a microscopic energy consumption model using second-by-second activity data from 38 Class 8 diesel drayage trucks operating in Southern California. The model emulated FCEV operations and determined an average hydrogen fuel consumption of 0.15 kg/mile across 749 trips. This data informed a levelized cost of …

Data And Ai Mystification: Ownership, Control, And Financialization In The Platform, Andrew W. Alexander

Faculty Research, Scholarly, and Creative Activity

The social relation between the platform and its users is defined by engagement with digital infrastructures and the rendition of this engagement into data. User-data, however, are surrounded by regulatory and legal ambiguities as they are not accounted for as intangible assets and their ownership and control are not transparent. I investigate how platforms rectify these ambiguities to realize user-data value as codified capital through an intensive case study of two major platforms. I use qualitative content analysis (QCA) to analyze annual and earnings reports, terms of service (ToS) agreements, and internal documents from 2017 through 2023 with qualitative data …

Explainable Use Of Foundation Models For Job Hiring, Vishnu S. Pendyala, Neha Bais Thakur, Radhika Agarwal

Faculty Research, Scholarly, and Creative Activity

Automating candidate shortlisting is a non-trivial task that stands to benefit substantially from advances in artificial intelligence. We evaluate a suite of foundation models such as Llama 2, Llama 3, Mixtral, Gemma-2b, Gemma-7b, Phi-3 Small, Phi-3 Mini, Zephyr, and Mistral-7b for their ability to predict hiring outcomes in both zero-shot and few-shot settings. Using only features extracted from applicants’ submissions, these models, on average, achieved an AUC above 0.5 in zero-shot settings. Providing a few examples similar to the job applicants based on a nearest neighbor search improved the prediction rate marginally, indicating that the models perform competently even without …

Effect Of Tai Chi Practice On The Adaptation To Sensory And Motor Perturbations While Standing In Older Adults, Arion Dey, Huiyeong Chang, Laila Shaaban, Armaan Suga, Genavieve Braden, Andres Bustamante, Jisang Park, Shenhua Zhang, Yang Hu, Manuel E. Hernandez

Faculty Research, Scholarly, and Creative Activity

Tai Chi provides an age-appropriate exercise to decrease fall risks in older adults. However, the exact mechanism underlying the benefits of Tai Chi practice remains an open question. Thus, this study examined how aging and Tai Chi practice impact adaptation to sensory and motor perturbations while standing. We hypothesized that older Tai Chi practitioners would exhibit a decreased reliance on visual processes as sensory and motor perturbations increased, relative to naive healthy older adults. Using rambling and trembling decompositions of the center of pressure (COP) and frequency-domain features, we examined changes in low (0–0.3 Hz), medium (0.3–1 Hz), and high …

Santa, Socials, And Secrets: Hard Cases For Epistemic Rights, Étienne Brown, Rebecca Chan

Faculty Research, Scholarly, and Creative Activity

In The Right to Know, Lani Watson forcefully argues in favor of recognizing epistemic rights to all humans. In this paper, we apply Watson’s framework to three hard cases. First, we consider interpersonal relationships and suggest that there is room to explore how epistemic rights bear on, e.g., whether parents can permissibly lie to or mislead their children by asserting the existence of Santa Claus. Second, we turn to social media platforms and contend that Watson’s framework is compatible with contrasting moderation policies and transparency requirements. Third, we examine a foundational case of legal ethics—the buried bodies case—which raises the …

The Impact Of Artificial Intelligence On Ecojustice And Ethics, Vishnu S. Pendyala

Faculty Research, Scholarly, and Creative Activity

Artificial Intelligence (AI) has attained human-level performance in tasks like text summarization, machine translation, and code generation while handling multimodal data. Despite these advances, AI poses challenges such as generating false or biased outputs, causing discrimination, and exhibiting opaque decision-making processes that hinder bias mitigation. Additionally, training large language models (LLMs) for AI consumes substantial energy and can enable autonomous warfare, posing a threat to eco-justice, and raising sustainability concerns. Their ability to create realistic content poses the risk of misuse and perpetuating misinformation. This article addresses these ethical issues and presents solutions through regulation and technology, with examples of …

Potential Of Co2 Sequestration Through Accelerated Weathering Of Limestone On Ships, Sijia Dong, William M. Berelson, Pierre Forin, Melissa Gutierrez, Dustin Carroll, Dimitris Menemenlis, Albert Y. Kyi, Jess F. Adkins

Faculty Research, Scholarly, and Creative Activity

Calcium carbonate dissolution is the dominant negative feedback in the ocean for neutralizing the acidity from rising atmospheric carbon dioxide. Mimicking this natural process, the accelerated weathering of limestone (AWL) can store carbon as bicarbonate in the ocean for tens of thousands of years. Here, we evaluate the potential of AWL on ships as a carbon sequestration approach. We show a successful prediction of laboratory measurements using a model that includes the most recent calcite dissolution kinetics in seawater. When simulated along a Pacific shipping lane in the Estimating the Circulation and Climate of the Ocean–Darwin ocean–general circulation model, surface …

Contributions Of California Teacher Librarians To Student Achievement, Keith Curry Lance, Caitlin Gerrity

Learning Hub

This article assesses the contributions of California Teacher Librarians (TLs) to student achievement, specifically in the area of English Language Arts and Literacy. This comparison-of-means analysis employed two major datasets: the California Department of Education (CDE) school library evaluation survey and California Assessment of Student Performance and Progress (CAASPP) data, both for the 2022-23 school year. This study found that students who met or exceeded ELA standards were more likely to be in schools with: a full-time, certified TL rather than a part-time TL or no TL; a TL–full- or part-time–rather than no TL; a TL staffing a single library …

Large Language Models For Quantitative Analysis Of Statutory Stringency And Its Correlation With Sexual Assault Crime Rates, Samhita Konduri, Vishnu S. Pendyala

Faculty Research, Scholarly, and Creative Activity

Sexual assault (SA) crimes are among the most important issues for our current society to solve, with these crimes in particular having long-term consequences on victims and their communities. To solve this issue, one approach is to make laws and penalties for these crimes stricter. However, there have not been any studies on the relationship between stricter penalties and lower crime rates, especially about SA crimes, in a quantitative manner. The biggest barrier to conducting a quantitative study on the strictness of laws and statutes is the lack of a standardized measure of how strict a legal text is. This …

Unraveling The Enigma Of Classification Of Synthetic And Genuine Information Using Machine Learning And Explainable Ai, Vishnu S. Pendyala

Faculty Research, Scholarly, and Creative Activity

There is a preponderance of AI-generated text everywhere today. Literature shows that there has been considerable success in detecting such text. This paper uses explainable AI (XAI) techniques to get insights into the workings of the machine learning models used to classify synthetic text. In detecting such text, this work analyzes synthetic and genuine information from visualization and explainability perspectives. The text is converted into vector embeddings using Robustly Optimized BERT Pretraining Approach (RoBERTa). Variational Autoencoders (VAEs) are used for visualization and Support Vector Machine (SVM) is used for classification. Local Interpretable Model-Agnostic Explanations (LIME), SHapley Additive exPlanations (SHAP), and …

Sunrise At The Salton Sea: Environmental Justice, Land Use Change, And Hydrosocial Dynamics Of Solar Energy Transitions In The Imperial Valley, California, Dustin Mulvaney, James J.A. Blair, Alida Cantor

Faculty Research, Scholarly, and Creative Activity

California's Imperial Valley, with lithium-rich geothermal brines, extensive flat agricultural fields with abundant desert sunshine, and access to transmission lines, is a leading case to explore interconnected themes around just energy transitions. Despite being the poorest county in California and one of the smallest, Imperial already provides 15% of the state’s solar electricity, and the region as a whole represents on the order of 25% of the state’s electric power capacity. This paper brings to light frictions over solar energy development that have emerged over the history of solar power development in the southern Salton Sea region. It describes the …

Volume 151, Issue 151, 2018, Megan Alfaro, Ursula K. Le Guin, Ahmed Moneim, Keenan Norris, Meg Tinsley, T.C. Boyle, Willy Lizarraga, Sophie Anne Berti, Sativa January, Susan Lowell, Brian Barrientez Ii, Steve H. Vu, Ellen Bass, James K. Zimmerman, Cb Follett, Joyce Schmid, James Brasfield, Meredith Davies Hadaway, Gustavo Hernandez, Marin Nelson, Silvia Bonilla, Katherine Morgan, Tommy Mouton, Sally Ashton, Anna Bernstein, Genevieve Deguzman, Suzanne Rico, Peyton Harvey, William Finnegan, Margaret Mcmullan, Don George, Clare Frank, Grace Schaffer, Robert D. Kirvel, Kelly Grogan, Kelley Jhung, Marisa Murrow, Terry Phimister, Sharon Simonson, Susan Shillinglaw, Talia Adry, Noelle Brada-Williams

Reed Magazine

No abstract provided.

Addressing Urban Traffic Congestion: A Deep Reinforcement Learning-Based Approach, Tairan Liu

Mineta Transportation Institute

In an innovative venture, the research team embarked on a mission to redefine urban traffic flow by introducing an automated way to manage traffic light timings. This project integrates two critical technologies, Deep Q-Networks (DQN) and Auto-encoders, into reinforcement learning, with the goal of making traffic smoother and reducing the all-too-common road congestion in simulated city environments. Deep Q-Networks (DQN) are a form of reinforcement learning algorithms that learns the best actions to take in various situations through trial and error. Auto-encoders, on the other hand, are tools that help simplify complex data, making it easier for the DQN to …

Strategized Reduction Of Greenhouse Gas Emissions Through Predicting And Extending The Service Life Of Concrete Pavements And Bridges, Fariborz M. Tehrani

Mineta Transportation Institute

Strong, durable concrete is key to resilient, long-lasting transportation infrastructure—especially in the face of climate change. This project explores innovative strategies for predicting and enhancing the service life of concrete in pavement and bridge systems, addressing the pressing need for sustainable transportation infrastructure. As concrete is pivotal to the durability and resilience of such structures, its environmental impact demands urgent attention. This project aims to reduce greenhouse gas emissions throughout their lifecycle by extending the service life of concrete pavements and bridge decks. A significant focus of the research is on the indications of chloride ion penetration in concrete, which …

Lse-Net: Integrated Segmentation And Ensemble Deep Learning For Enhanced Lung Disease Classification, Bhavan Kumar Basavaraju, Mohammad Masum

Faculty Research, Scholarly, and Creative Activity

Accurate classification of lung diseases is vital for timely diagnosis and effective treatment of respiratory conditions such as COPD, pneumonia, asthma, and lung cancer. Traditional diagnostic approaches often suffer from limited consistency and elevated false-positive rates, highlighting the demand for more dependable automated systems. To address this challenge, we introduce LSE-Net, an end-to-end deep learning framework that combines precise lung segmentation using an optimized U-Net++ with robust classification powered by an ensemble of DenseNet121 and ResNet50. Leveraging structured hyperparameter tuning and patient-level evaluation, LSE-Net achieves 92.7% accuracy, 96.7% recall, and an F1-score of 94.0%, along with improved segmentation performance (DSC …

On The Application Of Long Short-Term Memory Neural Network For Daily Forecasting Of Pm2.5 In Dakar, Senegal (West Africa), Ahmed Gueye, Serigne Abdoul Aziz Niang, Ismaila Diallo, Mamadou Simina Dramé, Moussa Diallo, Ali Ahmat Younous

Faculty Research, Scholarly, and Creative Activity

This study aims to optimize daily forecasts of the PM2.5 concentrations in Dakar, Senegal using a long short-term memory (LSTM) neural network model. Particulate matter, aggravated by factors such as dust, traffic, and industrialization, poses a serious threat to public health, especially in developing countries. Existing models such as the Autoregressive integrated moving average (ARIMA) have limitations in capturing nonlinear relationships and complex dynamics in environmental data. Using four years of daily data collected at the Bel Air station, this study shows that the LSTM neural network model provides more accurate forecasts with a root mean square error (RMSE) of …

The ‘Double-Exposure’ Of Riverine Communities In Northeast India To Dams And Climate Change, Costanza Rampini

Faculty Research, Scholarly, and Creative Activity

No abstract provided.

‘Making A Positive Environmental Impact’: Exploring The Role Of Volunteering At A Campus Community Garden, Dina Izenstark, Barbara Ann Boone

Faculty Research, Scholarly, and Creative Activity

Promoting sustainability in higher education is a social and environmental imperative. This paper explores how and why volunteering at a campus community garden (CCG) can serve as a unique context for promoting sustainability. Twenty-five undergraduate students between the ages of 18 and 27, who had volunteered at a campus garden, participated in individual semi-structured interviews. A majority of participants identified as female (80%) and Asian American (52%). Using reflexive thematic analysis, we first found students were motivated to volunteer for personal and academic reasons as well as to learn more about gardening. Childhood gardening experiences influenced participants’ re-engagement as adults. …

In Vitro Comparison Of Two Python-Based Programs For The Automated Analysis Of Tight-Junction Phenotype In Brain Endothelium During Bacterial Infection, Henry D. Mauser, Janessa Caroza, Shane Nicole Homez, Alyssa S. Arnett, William D. Cutts, Daryl W. Lam, Justin Thornton, Walter Adams, Brandon J. Kim

Faculty Research, Scholarly, and Creative Activity

Tight junction complexes are crucial features of brain endothelial cells, as they restrict the paracellular route across the blood–brain barrier. Tight junction disruption has been observed in conjunction with numerous diseases of the CNS. In such cases, the organization or integrity of cell–cell junctions may be analyzed with a variety of automated computer programs that quantitatively assess junction images. Here, we directly compare two previously developed python-based programs—JAnaP and IJOQ— for the semi- or fully automated analysis of tight junctions in human stem cell-derived brain-like endothelial cells. Cells were infected with S. pneumoniae and S. agalactiae to initiate junction disruption, …

Protecting Traditional Cultural Expressions: Law, Indigenous Protocols, Library Practices, Ulia Gosart, Valmaine Toki, Susan Townzen

Faculty Research, Scholarly, and Creative Activity

This study responds to contemporary international policy developments focused on protecting Indigenous creative work classified as Traditional Cultural Expressions. The study claims that states’ interests continue to guide policies in this area, compromising the relationship between regulations and the aspirations and needs of Indigenous communities. The study uses comparative methodology and content analysis to develop this argument. The study also highlights the significance of partnerships between Indigenous communities and cultural institutions that may function as alternative means to protect Indigenous creative works. The study explores cases from Indigenous communities and cultural institutions in New Zealand, the USA, and Mexico to …

Variability In Undergraduate Academic Stress: The Role Of Ethnicity, Early Adverse Family Experiences, And Psychological Distress, Teresa Mejia, Elana B. Gordis, Mitch Earleywine, Li Shen Chong

Faculty Research, Scholarly, and Creative Activity

Early adverse family experiences (e.g., abuse, neglect, and family conflict) can create vulnerabilities that can alter the association between psychological distress and academic stress, particularly for some ethnic groups. This study examined whether the link between psychological distress and academic stress varies in the presence of early adverse family experiences across ethnic groups. Participants (N = 284, 38.4% male, 59.5% female, 1% non-binary, and 0.7% transgender, 56.5% European American, 15.6% African American, 12.6% Hispanic and Latino, 8.5% Asian, 6.8% Mixed/Biracial) self-reported psychological distress, early adverse family experiences, and perception of academic stress. Regression analyses revealed a three-way interaction between adverse …

San Jose Urban Forest – An Open-Source Tree Canopy Surveying And Assessment Tool, Martin Alvarez Lopez, Manan Choksi, Sai Yaaminie Ganda, Vaibhavi Hiteshkumar Savani, Bernardo Flores

Faculty Research, Scholarly, and Creative Activity

The accurate monitoring of tree canopy coverage is crucial for social and environmental studies as well as city planning. Our goal is to provide a solution that utilizes available resources like yearly aerial imagery to generate tree data to track all tree canopy within a city such as San Jose, CA. By utilizing open-source software and publicly available data, we streamlined the process by eliminating the need for expensive equipment and time-consuming manual efforts associated with traditional methods. The methodology involves the conversion of aerial imagery datasets into geo-referenced TIFF format through a resampling process. To optimize efficiency, we strategically …

Domain-Specific Aspect Extraction For Product Design, Divyam Sobti, Mahima Agumbe Suresh, Cristina Tortora, Vimal Viswanathan

Faculty Research, Scholarly, and Creative Activity

As technology advances, computers become increasingly proficient at interpreting and translating human language into machine-understandable text. With the help of algorithms in natural language processing (NLP), machines can now translate textual data. These algorithms help identify and extract specific text components known as aspects. The aspects represent specific attributes or topics within textual data. For instance, if a product review states, “This phone has good battery life but poor camera quality, " and attributes like 'battery life' and 'camera quality' represent aspects in the text. Aspect extraction is a pivotal process involving identifying and isolating key features or topics within …

The Effectiveness Of Empowerment Versus Fear Messaging On Sugary Beverage Consumption Intentions Among Young Adult Latinas, Mi Zhou, A. Susana Ramírez, Dean Schillinger, Sandie Ha, Deepti Chittamuru

Faculty Research, Scholarly, and Creative Activity

Excessive sugar-sweetened beverage (SSB) consumption poses a significant public health concern, particularly among historically marginalized populations targeted by industry marketing. This study compares the effectiveness of empowerment-based versus fear-based messaging on individual sugary beverage consumption intention and critical health literacy among Latinas aged 18 to 29 years (N = 231). Participants were randomized online to view either an empowerment-based video highlighting the risks of sugary beverage consumption and the beverage industry’s manipulative practices or a usual care fear-based video centering on individual behaviors and risks. Between- and within-subject analyses were conducted using analysis of variance (ANOVA) and repeated ANOVA. Results …

Chains Of Equity: How Nationwide Injunctions Are Unconstitutional, Irfan Mohamed

Themis: Research Journal of Justice Studies and Forensic Science

Since the early judicial beginnings in the English Courts of Chancery, the principles of equity have guided judicial remedies for centuries. Modern American courts inherited these principles through reception statutes passed by newly independent states, which adopted English common law, including the concept of equity as a means of providing narrowly tailored remedies to resolve specific injuries. This paper examines the historical foundations of equity and argues that nationwide injunctions, which extend beyond the immediate litigants to affect the general public, are inconsistent with these principles and, therefore, unconstitutional. A historical and doctrinal analysis of the English Court of Chancery, …