Numerical Modeling of Climate Change Impacts on Transportation Embankments

Embankments are essential components of transportation infrastructure, providing crucial support for long stretches of highways, railways, and other routes in California and around the world. Clay embankments are susceptible to weather-related deterioration processes that can gradually compromise their stability and, in some cases, lead to unexpected failures. Climate change, along with the associated shifts in weather patterns, is projected to adversely impact the weather-related deterioration processes, leading to exacerbated failures and/or shorter service life. Additionally, climate change is projected to increase the frequency of extreme precipitation events, leading to an increase in embankment failure potential. This study evaluated (1) the effect of future climate scenarios on the long-term performance of clay embankments, and (2) the effect of extreme precipitation events brought about by future climate scenarios on the hydromechanical response of clay embankments to these extreme events. This study examined areas in central Los Angeles, California. Multi-phase hydromechanical geotechnical models were developed for exemplary high plasticity and low plasticity clay embankments with varied side slope angles. Overall, it was concluded that climate change is generally projected to adversely affect the performance of clay embankments both in the long-term and during extreme events, which can negatively impact critical national transportation infrastructure and disrupt the movement of people and goods

South Asians and Renal Disease: Traditional Food Lists for Management of Chronic Kidney Disease

The renal food list is a culturally tailored nutrition education tool designed to address the specific dietary needs of the South Asian population. It is an original intellectual work created by Ashwini Wagle, Ed.D., MS, RD, FAND, Chair and Professor, Department of Nutrition, Food Science, and Packaging at San José State University (SJSU). An earlier version of this tool was published in 2011 with the assistance of graduate student Kalpana Balasubramanian. The development of this renal food list was strengthened by the encouragement and support of the registered dietitian community, whose contributions included verifying the accuracy of the nutritional information and ensuring the authenticity of the traditional foods represented.https://scholarworks.sjsu.edu/oer/1019/thumbnail.jp

Henze, Rosemary C.

Stanford University, Education (Language, Literacy & Culture), Ph.D. 1988 San Francisco State University, English (TESL), M.A. 1980 University of California, Santa Cruz, Art, B.A. 1974https://scholarworks.sjsu.edu/erfa_bios/1372/thumbnail.jp

Archeota, Fall/Winter 2025

Archeota is a platform for SJSU iSchool students to contribute to the archival conversation. It is written BY students, FOR students. It provides substantive content on archival concerns and issues and promotes professional development in the field of archival studies. Archeota upholds the core values of the archival profession. Contents: Unrecorded Legacies: Why Masonic Archives Matter by Audie Robinson, Book Review: Decolonial Archival Futures by Vanessa Sztym, Passports to the Past: Following the Trail of Sacramento’s Archives Crawl by Emily Stockton, Volunteering at the Jack Mason Museum of West Marin History: Beginnings and Belonging by Heather Arnold, Images From The Front: A Reflection on Digitizing a Partially Processed Archival Collection by Niamh Tangney, Field Notes from the Archives Fellow at the Center for Puerto Rican Studies by Gianna Elena Brassil, Farewell to Our Fall 2025 Graduates, Meet the 2026 Archeota Team, SAASC Spring 2026 Executive Board, SAASC Fall & Winter 2025 Eventshttps://scholarworks.sjsu.edu/saasc_archeota/1023/thumbnail.jp

Spartan Daily, March 5, 2025

Volume 164, Issue 18https://scholarworks.sjsu.edu/spartan_daily_2025/1017/thumbnail.jp

Spartan Daily, February 18, 2025

Volume 164, Issue 11https://scholarworks.sjsu.edu/spartan_daily_2025/1010/thumbnail.jp

Inspection Technologies for Construction and Maintenance of Highway Infrastructure – Review and Analysis

The Federal Highway Administration (FHWA) and state Departments of Transportation (DOTs) seek to provide high quality infrastructure that meets or exceeds the desired quality standards crucial for ensuring safety and efficiency in our nation\u27s transportation systems. Efficient inspection practices—which enable conformance with plans, specifications, and quality standards—are an essential part of this effort. In this digital age, state DOTs are relying on emerging technologies to improve inspection practices. However, there is limited knowledge available regarding various emerging technologies used for highway infrastructure construction and maintenance inspection. This study identifies various emerging technologies that are implemented at the state DOTs and their uses/applications for various inspection purposes. The emerging technologies studied in this project include Remote Sensing and Monitoring Technologies—specifically, Unmanned Aerial Systems (UASs) and Light Detection and Ranging (LiDAR)—as well as Building Information Modelling (BIM), and Augmented Reality and Virtual Reality (AR/VR). Based on a comprehensive literature review and content analysis of journal articles, technical reports, state DOT documents/reports, templates, and guidelines on the identified technologies, the research findings indicate different usage levels among state DOTs and found that DOTs use these technologies for applications such as structural inspection, verifying quantities, bridge and visual inspection, safety inspection, inspection workforce training, inspection documentation, and measurements of pay quantities, among others. This study serves as a valuable resource for state DOTs seeking to maximize the benefits of their investments and embrace innovative inspection technologies to ensure safety and efficiency in the nation\u27s transportation infrastructure

The Impact of Artificial Intelligence on Data Privacy: A Risk Management Perspective

Purpose: The purpose of this paper is to increase the artificial intelligence (AI) ethical literacy of information governance professionals by explaining how AI intensifies familiar data privacy issues by virtue of its dependency on data and ability to create new personal information, to explicate emerging privacy enhancing methods and to show their continuity with existing privacy and information governance principles. Design/methodology/approach: The paper uses an interdisciplinary design research methodology that extends current governance frameworks by combining information science, information governance and applied ethics concepts. Three information sources were referenced: 1) academic papers; 2) standards and best practices published by governmental and nongovernmental organizations and professional associations; and 3) white papers, market research and vendor reports. The literature review was informed by real-world implementation knowledge and anecdotal evidence to identify privacy risks when using AI. Useful tools, techniques and governance approaches to manage and mitigate the risks associated with digital privacy and ethics when using AI are identified and discussed. Findings: The paper analyzes the relationship between different approaches to AI (e.g. symbolic-deductive, machine learning and deep learning) and levels of privacy risks. It identifies risk reduction methods (e.g. differential privacy) and relates these to extant privacy principles such as data minimization. Finally, the paper shows the continuity between information governance practices and newly emerging AI governance and risk frameworks. Originality/value: The authors present useful tools and techniques and discuss them from a business perspective, using the lens of information governance to mitigate AI-related privacy risks. The authors also discuss how design techniques and technologies can help minimize data collection of sensitive information and can be used to anonymize sensitive data when training AI models

Information Strategies in the Electric Vehicles Battery Reverse Supply Chain with Blockchain Technology

The surge in demand for electric vehicles (EV) and EV batteries, coupled with supply chain vulnerabilities and price instability, has driven the need for efficient and sustainable EV battery recycling processes. This report investigates the potential of blockchain technology to address the challenges in the EV battery reverse supply chain (moving goods from the end customer back towards the manufacturer), focusing on enhancing transparency and coordination, as well as mitigating the impact of unregulated recycling. Key stakeholders in this analysis include manufacturers, recyclers, and regulatory bodies. To achieve these objectives, the study employs a mixed-methods approach. It includes semi-structured interviews with industry experts from EV and battery manufacturing companies to gather qualitative insights into the current challenges and the potential of blockchain technology. Furthermore, the study used a model based on the Stackelberg game theory to analyze the impact of blockchain adoption on the behavior and profitability of supply chain members, specifically focusing on the interaction between regulated and unregulated recyclers. The findings show that blockchain technology can offer significant benefits to the EV battery reverse supply chain. Specifically, blockchain adoption can increase the total recycling quantity, provided that the implementation costs are relatively low. Additionally, blockchain can help empower regulated recyclers to achieve higher buyback prices and recycling quantities compared to unregulated recyclers, enhancing the competitiveness of responsible recycling practices. However, the adoption of blockchain technology depends on its cost-effectiveness and the intensity of competition within the recycling sector. These results highlight the importance of strategic blockchain implementation and regulatory support to foster a sustainable and efficient EV battery recycling ecosystem, which supports a sustainable transportation industry