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Seeing Through Their Eyes: Photovoice Insights from Marginalized Students in Academic Libraries
No full textThis study explores self-identified Asian and Indigenous undergraduate students' perceptions of space and the environment at the Meriam Library at California State University (CSU), Chico, a rural, mid-size public university. Through photovoice, a qualitative research methodology, librarians sought Indigenous and Asian students' perceptions of the library. Photovoice is a research method that prompts students to take photos at the library and discuss their images in small group interviews. The data gathered from the photos and interviews is analyzed and coded into overarching themes for the library to assess and act on
Spatiotemporal patterns and abiotic influence on bat activity on Santa Rosa Island, California
Get PDFThere is a research gap in our understanding of bat ecology and behavior on islands. Bats uphold ecosystem balance by providing ecosystem services, including insectivory, pollination, and seed dispersal. These processes are especially important on Santa Rosa Island (SRI), California, which is recovering from an intensive ranching era that decimated native vegetation. Greater bat biodiversity could indicate island recovery, as well as show the suitability of SRI as habitats for them during migration periods.We deployed passive acoustic monitoring detectors at the National Park Service (NPS) nursery, and the Santa Rosa Island Research Station (SRIRS) bunkhouse, which are triggered by echolocation calls to start recording bat passes. The goal of the study was to investigate spatiotemporal patterns of bats on SRI, as well as abiotic factors that may influence their activity. We detected 12 of 14 bat species identified by Brown and Rainey on the Channel Islands in 2018, and classified any other bats as migratory species. When comparing the activity indices and species composition of the different sites, we found that resident bats were not significantly more active than migratory bats at the nursery, but they were the most active at the bunkhouse. Existing studies show that bats are highly responsive to changing abiotic factors, including wind and lunar illumination, which vary greatly on SRI. Our results confirmed that wind, after accounting for lunar illumination, significantly reduced bat activity. We detected twenty-two migratory species across the two field sites, including the federally endangered gray bat (Myotis grisescens). This information serves as a starting point for the manual identification of live specimens. Our findings may help identify biodiversity hotspots on the island and inform conservation decisions, as well as contribute to the greater body of knowledge on bat behavior and habitat preferences
Mapping Chemical Stimuli to their Cognate Neurons in Pristionchus pacificus using Genetically-Encoded Calcium Indicators
No full textNematodes have amphid sensory neurons that allow them to sense various chemical stimuli in their environment that could be indicative of nearby food, danger, or other organisms. Two model nematode species Caenorhabditis elegans and Pristionchus pacificus share the exact same number of homologous amphid neurons, but exhibit vast differences in their chemosensory profiles, neuron morphology, and ecology. While amphid neurons and their corresponding sensory stimuli are well-described in C. elegans, a neuronal map characterizing the various sensory modalities does not yet exist for P. pacificus. Therefore, the aim of this study is to map chemical stimuli to their cognate amphid neurons in P. pacificus. We generated transgenic nematodes that express genetically encoded calcium indicators (GECIs) and conducted calcium imaging experiments to measure neuronal activity while worms were exposed to chemical stimuli, i.e., volatile odorants and salt tastants. Here we demonstrate that the P. pacificus AM7 neurons respond asymmetrically to salts (NH4Cl, NH4I, and NaCl), most likely via the GCY-22.3 receptor. Surprisingly, we found that the putative thermosensory AM12 neurons are also responsive to salts. However, our results for the AM9 and AM11 neuronal responses to salts and odors were inconclusive. Additional experiments with an expanded array of chemical stimuli are required to further reveal the chemosensory functions of these neurons, and ultimately to improve comparisons of sensory systems between different nematode species and their evolutionary drivers
Rivers Along an Urban Gradient: A Comparative Study of Plant and Arthropod Assemblages in the Novel Los Angeles River and Less Urbanized Riparian Ecosystems
No full textInside one of southern California's most urbanized watersheds, an isolated riparian ecosystem structured more by human influence than by natural processes persists in several soft bottom stretches of the otherwise concrete lined channel of the Los Angeles River. Despite decades of increasing public and governmental interest in restoring the heavily urbanized river to a more natural state, our understanding of the ecological processes within this novel ecosystem is limited. To address this, I collected vegetation data and sampled terrestrial arthropods with pitfall traps in the Los Angeles River's soft bottom habitat at the Glendale Narrows, as well as the riparian forests of other major southern California waterways, specifically the Santa Ana and Santa Clara Rivers. By comparing the taxonomic and functional diversity of these riparian communities to those in the Los Angeles River, I gained insights into how this novel ecosystem differs from other low to moderately urbanized rivers in southern California. Reflecting its heavily urbanized disturbance regime, the Los Angeles River's vegetation was distinct from that of the Santa Ana and Santa Clara Rivers, deficient in native cover, and was dominated by non-native and ruderal vegetation. Similarly, while the arthropod assemblages at the Los Angeles River were functionally similar to those at the less urbanized rivers, they were less taxonomically diverse, had fewer predator and detritivore taxa, and exhibited lower evenness, with many functional groups dominated by non-native taxa. These findings suggest that the Los Angeles River's novel soft-bottom ecosystem lacks the ecological redundancy found in more natural systems, potentially making its communities less stable, less resilient in the face of disturbances, and likely reducing the quality of the ecosystem services it provides. Given the effectiveness of arthropods as indicators of successful restoration, these insights provide an ecological baseline for future in-channel enhancement efforts aimed at improving the biodiversity and ecological functionality of this novel ecosystem
A Comprehensive Testing Approach using Jest for React Native Mobile Applications
No full textThis paper highlights the importance of ensuring the seamless execution of mobile applications. Mobile apps heavily depend on quick and reliable responses to any issues, as even minor bugs or glitches can significantly affect the user experience. Traditional testing methods often fall short, leaving room for improvement in user satisfaction. Variations in app performance and stability across different screen sizes can lead to inconsistencies that negatively impact the user experience. This project addresses these challenges through a comprehensive testing approach, focusing on critical app features such as login and registration functionalities. It emphasizes configuration procedures, user preferences, and the utilization of the JEST assessment tool for rigorous testing. The approach includes a system for integration and deployment to enhance dependability and efficiency. The final phase involves user testing to demonstrate the effectiveness of the solution. The aim is to deliver a platform that ensures usability and reliable performance in real-life scenarios, with a user-friendly mobile interface designed to meet diverse needs. This project is part of the Smart Textile initiative at ARCS, focusing on testing a smart wearable mobile application for the Smart Textile project. It was conducted under the guidance and leadership of esteemed faculty members involved in the Smart Textile project. Their expertise and support were instrumental in the successful execution of this research
Three region analytical models for GaAs MESFET in Low Voltage Digital circuits
Get PDFThis research project addresses MESFET properties of Gallium Arsenide, particularly with regard to high-frequency performance and power management, design and analysis of which in terms of terminal voltages, it offers analytical models that faithfully anticipate MESFET current-voltage behavior in important areas of operation including subthreshold, linear, and saturation, therefore enabling exact and effective modeling of MESFETs. It improves the low-voltage digital circuit performance and design. Key to this is simulating MESFET's behavior in linearity and saturation concerning many gates and drain-source voltage. Important in high-performance RF and microwave communications applications, current flow and stability are optimized using advanced mathematical modeling and simulations. Short-channel effects are considered in the models created inside the framework of this research, therefore improving predictions for such events as threshold voltage changes and velocity saturation under strong fields. This method has shown that MESFETs function better on undoped substrates, providing higher noise margins and thus perfect fit in high-density digital circuit applications. These findings provide researchers and engineers working on advanced semiconductor devices and low-voltage digital circuit design useful insights and practical too
Analytical Modeling of Gate-Voltage Dependence on Source/Drain Series Resistances and Effective Gate Length in GaN MESFETs
Get PDFThis graduate project aims to develop an analytical model that presents the gate-voltage (VG) dependence on source and drain resistances (Rs and Rd, respectively) as well as the dependence on the effective gate length (Lg,eff) of Gallium Nitride (GaN) MESFETs. These devices have significant applications due to their high electron mobility and breakdown voltage. However, an in-depth understanding of how gate voltage affects Rs, Rd, and Lg is critical for optimizing device performance. This study also investigates the intrinsic modulation of charge in the gated and ungated portions of the device, which all contribute to variations in Lg as a function of gate voltage. Additionally, the project aims to address the impact of these variations on the series resistances, which are essential parasitic elements that influence device efficiency and reliability. By incorporating these into an analytical model, they will provide insights that are essential to the design of GaN MESFETs. This project is organized as follows: CHAPTER 1 provides an introduction to MESFET devices, Gallium Nitride material, the effect of radiation on GaN, and GaN MESFET's superior switching speed, power, and frequency performance. CHAPTER 2: provides an in-depth view of GaN material structure, its energy band as compared to other materials, and material and device fabrication. CHAPTER 3: delves into the internal characteristics of a GaN MESFET, which include the small and large signal models, the importance of transconductance (Gm) on device performance, and the phenomena known as on-resistance (RDS(ON)), which is directly correlated to the overall power dissipation on a device. CHAPTER 4: provides models which break down the current-voltage (I-V) characteristics of a MESFET device and its performance in high-frequency applications, and the gate-voltage dependence to the drain-to-source resistance (Rdsi(Vg)) and effective gate length (Lg,eff), countering more conventional model assumptions. CHAPTER 5: and CHAPTER 6: depict the results and conclusion of the analytical models with generated plots. The references are cited in CHAPTER 7: and lastly, CHAPTER 8: contains the MATLAB source code used to generate the plots for the I-V Characteristics and Vg dependences on Rdsi and Lg,eff
Measuring the impact of sea otter presence and activity on eelgrass system health in Morro Bay, CA: The creation of a novel otter-eelgrass index
Get PDFThe Morro Bay estuary, a semi-enclosed 2,300-acre habitat separated from the Pacific Ocean by a vegetated sandspit, hosts key ecosystem engineer species such as eelgrass (Zostera marina) and the southern sea otter (Enhydra lutris nereis). Eelgrass provides essential ecosystem services, enhancing both ecological and social resilience. The southern sea otter, a keystone predator, contributes to eelgrass meadow productivity through bioturbation, which increases genetic diversity in the sediment and supports eelgrass adaptation to climate change-driven disturbances. It was found that sea otter presence and grooming activity influence eelgrass health in Morro Bay, notably affecting supporting, regulating, and provisioning ecosystem services. Otter presence, especially when coupled with grooming activity, most significantly impacts shoot count and chlorophyll-a production levels in eelgrass. A novel index, the Sea Otter Presence Impact on Eelgrass index (SOPIE), was developed to quantify the otter-eelgrass relationship, revealing that the Coleman transect exhibited the highest levels of otter impact on eelgrass system health compared to the North Sandspit and Morro Rock Otters transects. Observations suggest that sea otters use the Morro Rock eelgrass system primarily for rest and revival, while reserving foraging and feeding activities for the North Sandspit and Otter Sandspit areas. Future research should continue exploring this otter-eelgrass interaction with larger sample sizes, consistent otter activity data collection, and expanded locations within Morro Bay, particularly targeting sea otter hotspots. Additionally, analyzing potential spatio-temporal trends across transects could further the understanding of this relationship, contributing to conservation efforts and ecosystem management strategies for both eelgrass and sea otters in the estuary
Using TinyML for the detection of Irregularities
Get PDFThis project investigates two machine learning methods for anomaly detection in home electrical appliances, specifically targeting a fan. Using accelerometer data collected from normal and anomalous fan operations, we first implemented a Mahalanobis Distance-based statistical model, which evaluates anomalies by comparing data against normal behavioral distributions. Subsequently, we explored an Autoencoder neural network, built using TensorFlow and Keras, which reconstructs expected operational patterns and flags deviations as anomalies. Both models were deployed on an ESP32 microcontroller for real-time inference at the edge, using TensorFlow Lite to support the Autoencoder. Testing each approach revealed that, while the Mahalanobis model is straightforward and efficient, the Autoencoder proved more robust in handling diverse operational states. This work underscores the potential of TinyML to enable practical, low-latency anomaly detection in resource-constrained devices, enhancing predictive maintenance in everyday appliances
Effect of Green Marketing on Green Trust and Green Perceived Value in the Fashion Industry
No full textThe fashion industry is experiencing exponential growth, fueled by increasing consumer demand for clothing. However, this growth has resulted in environmental challenges, with the fashion industry contributing significantly to carbon emissions and water pollution. In response to consumer awareness of these issues, green marketing has become prevalent among clothing companies, aiming to promote sustainability and appeal to environmentally conscious consumers. Despite this trend, previous research suggests that consumers often find green marketing confusing or unreliable. This thesis investigates the effectiveness of green marketing claims in the fashion industry using Signaling Theory, focusing on their impact on consumers' green trust and green perceived value. Drawing from Carlson, Grove, and Kangun's advertising matrix, four types of advertising claims (product orientation, process orientation, image orientation, and environmental fact) are examined alongside different visuals in advertisements. The study utilized a 4x2 experimental design, presenting participants with various combinations of advertising claims and imagery, followed by surveys to assess their perceptions. The results revealed no significant impact of green visuals, or the four types of advertisement claims on consumers' green trust or green perceived value. Contrary to prior research suggesting the efficacy of sustainability signals in marketing, this study suggests that consumers may have become desensitized to sustainability messaging. The increasing prevalence of greenwashing could contribute to this desensitization, as consumers demand more verifiable evidence of brands' environmental efforts. Additionally, a correlation analysis indicated a significant positive relationship between green trust and green perceived value and a positive correlation between both variables and new clothes shopping frequency. This suggests that while consumers with higher trust perceive greater value in green products, those who shop more frequently tend to develop a deeper appreciation for green marketing efforts. These findings provide valuable insights for marketers in the fashion industry, emphasizing the need for more transparent and authentic sustainability communication. Instead of relying on vague claims or appealing imagery, brands should focus on providing verifiable proof of their environmental commitments to foster genuine consumer trust. Further research should explore the role of third-party certifications and more diverse consumer demographics to enhance the understanding of effective green marketing strategies in the fashion industry