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From Tree to Shrub? The Fate of Tanoak through Fire and Nonnative Disease
No full textInvasive plant pathogens have killed an uncountable number of trees and disrupted ecosystem processes throughout the world. Newly introduced pathogens may interact with historically occurring disturbances in unexpected ways to cause amplified mortality and change to ecosystem processes. Here, I examine the a natural experiment created by three wildfires in Big Sur, a portion of the central coast of California impacted by the nonnative pathogen Phytophthora ramorum, to forecast the future of a species susceptible to the pathogen. Using a plot network which spans the length of Big Sur, I track the survival of individual tanoak (Notholithocarpus densiflorus) stems and trees over a 12-year period in areas with various fire and disease histories. Large, old tanoak stems are killed by P. ramorum infection, which causes a disease known as sudden oak death. Young stems are vulnerable to fire. My results indicate that the combination of this novel pathogen and fire results in high mortality of existing tanoak stems of all size classes followed by energetic sprouting of new stems, converting the tanoak from a large overstory tree to a multi-stemmed shrub. This new form alters the fuel quantity and distribution within affected stands and may influence future fire behavior in the central coast region of California
Introduction: Facing the Challenge of AI with Feminist Pedagogy
No full textThis special issue truly faces the challenge of AI with feminist pedagogy. The introduction briefly summarizes the five critical commentaries, five original teaching activities and three book reviews that make up this issue on AI
Behind the Prompt: The Environmental Impact of LLM Inference
No full textAs the size and demand for large language models (LLMs) increase, the environmental impact of computational inference often exceeds training; yet industry lacks a standardized method of calculating this expanding environmental footprint. Complexity arises with task-specific computational demands, infrastructure overhead, and various GPU architectures, making cross-model assessments burdensome. Combining environmental engineering and computer science principles by validating Jegham et al.’s meta-model, we predict the carbon emissions and water consumption during inference, providing metrics to raise user awareness of AI’s growing environmental footprint. Additional work supports integration into a multi-agent conversational system that encourages responsible scheduling and prompting, guiding the user towards sustainable AI solutions. Our results show that this framework can predict carbon emissions and water usage during inference across a variety of LLM architectures and sizes with reasonable accuracy for both locally-running and proprietary cloud-based LLMs
Short-Arc Angles-Only Initial Orbit Determination for LEO and GEO Objects Using a Genetic Algorithm
No full textAn ever-growing interest in utilizing space for scientific, commercial, and defense applications has led to an exponential rise in orbital debris recent years. With this sharp increase in space objects comes a greatly increased risk of potential collisions, necessitating an increase in Space Situational Awareness. In order to best mitigate the risk of future collisions in an increasingly congested space environment, it is crucial to be able to accurately determine the orbits of these new objects for trajectory tracking. This process is initial orbit determination (IOD), and is especially difficult when only observation angles are available for short observation times. This thesis analyzed the accuracy of multiple variations of an IOD method using a genetic algorithm, a stochastic optimization metaheuristic mimicking natural selection. Gauss’s method, a well-researched classical IOD, was used as a baseline for analysis. Particular consideration was given towards the number of observation points available as well as the consequences of assuming a circular orbit. It was found that an assumed-circular orbit genetic algorithm IOD was nearly 100% successful in predicting secondary observations for the majority of the examined test cases with eccentricities up to 0.13, with limitations occurring at extremely short-arc, coplanar data. The GA was found to produce solutions with far less variability than Gauss’s method when dealing with noisy observation data, with Gauss’s method failing to converge to solutions for much of the GEO data
Building an Inclusive AI Chatbot for Diverse Student Communities at Cal Poly: Uplift AI
No full textThis research project will investigate the ability of advanced Large Language Models (LLMs) to identify and assess misinformation across diverse forms of media, including text, images, and video. In an age where misleading content spreads rapidly across digital platforms, evaluating the reliability and integrity of AI systems tasked with fact-checking is critical. We will develop a comprehensive dataset composed of factual and misleading examples drawn from various well-known and reliable fact-checking organizations. Each item will be independently reviewed and transparently labeled to ensure reproducibility. We will then prompt a curated group of state-of-the-art LLMs—including GPT-4, Claude, Gemini, Perplexity, Grok, and Meta\u27s LLaMA—to return a misleadingness score and a self-reported confidence score for each item. These responses will be evaluated against ground-truth labels to assess each model\u27s accuracy and consistency. Ultimately, we will develop a tool that allows users to input various types of media. The tool will then collect responses from multiple LLMs and use a statistical model to determine its own score for how misleading the information is and the confidence in that statement. This tool will use LLMs to fact-check other LLMs, avoiding bias or hallucination from a single inaccurate answer/model. The project emphasizes reproducibility, open-source tooling, and ethical safeguards to ensure that all findings are verifiable and responsibly communicated
Effects of Temperature and Oxygen Stress on Two Populations of Olympia Oysters (Ostrea lurida) from Central California
No full textOlympia oysters (Ostrea lurida) are the only native oyster species to the North American West Coast. A once thriving species, O. lurida populations have dramatically declined over time due to factors such as overharvesting, habitat degradation, and the introduction of invasive predators. Although their populations are still present in estuaries along their habitat range, many of these same stressors persist today, preventing the re-establishment of dense oyster beds and hindering recovery of populations. Among these current day stressors, a major concern are the impacts of climate change, specifically warming water temperatures and the increased frequency of hypoxic events. As sessile organisms in the low intertidal and shallow subtidal zones, O. lurida are especially vulnerable to the conditions of their variable environment. Two Central California O. lurida populations from Elkhorn Slough and Morro Bay estuaries were identified as high priority sites for O. lurida conservation aquaculture. Future conservation aquaculture strategies may employ crossbreeding of two O. lurida populations to enhance broodstock quality and grow population sizes within each estuary. However, to proceed with this strategy, we must first evaluate potential local adaptations as well as climate change resiliency within each source population. This study set out to explore whether there were differences between the Elkhorn Slough and Morro Bay O. lurida populations when exposed to elevated temperature and low oxygen stress. To explore this, we compared responses of O. lurida from these populations to elevated water temperature (22°C) and anoxia (0 mg O2/L) on survival, enzyme activity of certain biochemical indicators of metabolic strategy [PK:PEPCK activity], oxidative stress response [tAOX], and gene expression patterns. We found significant population differences in survival: Morro Bay O. lurida survived longer than those from Elkhorn Slough under anoxia challenges. Enzyme measurements of PK:PEPCK activity indicated distinct metabolic strategies, with Morro Bay O. lurida maintaining greater reliance on aerobic metabolism, while Elkhorn Slough O. lurida maintained greater reliance on anaerobic metabolism. We did not find significant differences in oxidative stress response by measurement of tAOX. Comparative transcriptomics utilizing differential gene expression analysis found population-specific and shared patterns of transcriptional response to elevated temperature and oxygen limitation challenges. Both populations exhibited mostly shared gene expression patterns suggesting limited evidence for local adaptations to these stress challenges. Weighted gene correlation network analysis emphasized the significant and broad transcriptional responses to oxygen limitation but interestingly not to temperature. These findings suggest that the two populations show limited evidence of divergent local adaptations and physiological responses to elevated temperature and anoxia. Consequently, Elkhorn Slough O. lurida populations may benefit from receiving Morro Bay O. lurida to enhance broodstock quality, providing a practical strategy for their conservation
BAJA SAE Brakes
No full textHistorically, the Cal Poly Racing Baja SAE has produced a braking system that has proven unreliable and barely passes competition rules and inspections, leading to ill performing and unsafe brakes. The goal of this project is to produce a system and documentation that meets the requirements provided by Cal Poly Racing Baja SAE. The final design includes a transient braking model of the vehicle to set system requirements, universal custom front and rear calipers modified from “Cal Poly BSAE Custom Brake Caliper Senior Project”, and a revamped hydraulic harness. Leaning on the team’s previous work and modifying the custom calipers allowed us to focus our efforts on the system’s complexity and reliability as a whole. We then manufactured and assembled the components of the brakes system and integrated them onto the CPX 25 car. The next steps were to test the components and make design changes based on the successes and failures of the car before competition. The car then was taken to the two BAJA SAE competitions that Cal Poly Racing competed in, passing brake check both times with no failures
On Sobolev Spaces and the Existence of Weak Solutions to Boundary Value Problems
No full textMany boundary value problems that arise in mathematical models have close connections to second order elliptic partial differential equations. This thesis introduces the idea of weak derivatives and Sobolev Spaces to generalize possible solutions. Using functional analysis centered around the Lax-Milgram theorem, we show the existence of these generalized solutions to boundary value problems including Laplace\u27s Equation, 2nd order linear ODEs, and ultimately a general second order elliptic PDE. The work cumulates with recovering a number of central theorems of functional analysis in the context of Sobolev Spaces, creating a new perspective on the solvability of these boundary value problems