Digital Commons Network^™

Participation In Collaborative Fisheries Research Improves The Perceptions Of Recreational Anglers Towards Marine Protected Areas, Erin M. Johnston, Grant T. Waltz, Rosamaria Kosaka, Ellie M. Brauer, Shelby L. Ziegler, Erica T. Jarvis Mason, Hunter S. Glanz, Lauren Zaragoza, Allison N. Kellum, Rachel O. Brooks, Brice X. Semmens, Christopher J. Honeyman, Jennifer E. Caselle, Lyall F. Bellquist, Sadie L. Small, Steven G. Morgan, Timothy J. Mulligan, Connor L. Coscino, Jay M. Staton

Faculty Research, Scholarly, and Creative Activity

Collaborative fisheries research programs engage stakeholders in data collection efforts, often with the benefit of increasing transparency about the status and management of natural resources. These programs are particularly important in marine systems, where management of recreational and commercial fisheries have historically been contentious. One such program is the California Collaborative Fisheries Research Program (CCFRP), which was designed in 2006 to engage recreational anglers in the scientific process and evaluate the efficacy of California’s network of marine protected areas. CCFRP began on the Central Coast of California and expanded statewide in 2017 to include six partner institutions in three regions: …

Tracked Gulls Help Identify Potential Zones Of Interaction Between Whales And Shipping Traffic, Megan A. Cimino, Heather Welch, Jarrod A. Santora, David Kroodsma, Elliott L. Hazen, Steven J. Bograd, Pete Warzybok, Jaime Jahncke, Scott A. Shaffer

Faculty Research, Scholarly, and Creative Activity

Seabird-vessel interactions are often studied through the lens of fisheries bycatch, but seabirds encounter many watercraft types. Western Gulls Larus occidentalis breeding on the Farallon Islands (California, USA) have a foraging domain that encompasses both shipping lanes and productive fishing grounds, resulting in ample opportunities for vessel encounters. Previous research showed that these Western Gulls can serve as ecosystem indicators because their foraging behavior is linked to ocean prey conditions, and because their foraging grounds overlap with that of Humpback Whales Megaptera novaeangliae, which can make prey accessible. Because ship strikes and entanglement in fishing gear are concerns for whales …

Cross-Cultural Adaptation Of The Voice-Related Experiences Of Nonbinary Individuals - Veni To Brazilian Portuguese, Isabela Dos Santos, Mara Behlau, Grace Shefcik, Pei Tzu Tsai, Vanessa Veis Ribeiro

Faculty Research, Scholarly, and Creative Activity

Purpose: This study aimed to translate and cross-culturally adapt the “Voice-related Experiences of Nonbinary Individuals” (VENI) to Brazilian Portuguese (BP). Methods: Cross-cultural adaptation was performed based on the combined guidelines of the World Health Organization’s (WHO) Translation Recommendations and the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). The process included five stages: a) Translation of the instrument into BP by a translator specialized in the construct and a non-specialist, both native BP speakers and fluent in English; b) Synthesis of the two translations by consensus; c) Back-translation by a translator specialized in the construct and a non-specialist, …

Evaluating The Influence Of Marine Protected Areas On Surf Zone Fish, M. L. Marraffini, S. L. Hamilton, J. R. Marin Jarrin, M. Ladd, G. Koval, J. R. Madden, I. Mangino, L. M. Parker, K. A. Emery, K. Terhaar, D. M. Hubbard, R. J. Miller, J. E. Dugan

Faculty Research, Scholarly, and Creative Activity

Marine protected areas (MPAs) globally serve conservation and fisheries management goals, generating positive effects in some marine ecosystems. Surf zones and sandy beaches, critical ecotones bridging land and sea, play a pivotal role in the life cycles of numerous fish species and serve as prime areas for subsistence and recreational fishing. Despite their significance, these areas remain understudied when evaluating the effects of MPAs. We compared surf zone fish assemblages inside and outside MPAs across 3 bioregions in California (USA). Using seines and baited remote underwater videos (BRUVs), we found differences in surf zone fish inside and outside MPAs in …

A Fresh Take: Seasonal Changes In Terrestrial Freshwater Inputs Impact Salt Marsh Hydrology And Vegetation Dynamics, Maya S. Montalvo, Emilio Grande, Anna E. Braswell, Ate Visser, Bhavna Arora, Erin C. Seybold, Corianne Tatariw, John C. Haskins, Charlie A. Endris, Fuller Gerbl, Mong Han Huang, Darya Morozov, Margaret A. Zimmer

Faculty Research, Scholarly, and Creative Activity

Salt marshes exist at the terrestrial-marine interface, providing important ecosystem services such as nutrient cycling and carbon sequestration. Tidal inputs play a dominant role in salt marsh porewater mixing, and terrestrially derived freshwater inputs are increasingly recognized as important sources of water and solutes to intertidal wetlands. However, there remains a critical gap in understanding the role of freshwater inputs on salt marsh hydrology, and how this may impact marsh subsurface salinity and plant productivity. Here, we address this knowledge gap by examining the hydrologic behavior, porewater salinity, and pickleweed (Sarcocornia pacifica also known as Salicornia pacifica) plant productivity along …

Episodic Memory Assessment: Effects Of Sex And Age On Performance And Response Time During A Continuous Recognition Task, James O. Clifford, Sulekha Anand, Franck Tarpin-Bernard, Michael F. Bergeron, Curtis B. Ashford, Peter J. Bayley, John Wesson Ashford

Faculty Research, Scholarly, and Creative Activity

Introduction: Continuous recognition tasks (CRTs) assess episodic memory (EM), the central functional disturbance in Alzheimer’s disease and several related disorders. The online MemTrax computerized CRT provides a platform for screening and assessment that is engaging and can be repeated frequently. MemTrax presents complex visual stimuli, which require complex involvement of the lateral and medial temporal lobes and can be completed in less than 2 min. Results include number of correct recognitions (HITs), recognition failures (MISSes = 1-HITs), correct rejections (CRs), false alarms (FAs = 1-CRs), total correct (TC = HITs + CRs), and response times (RTs) for each HIT and …

Is Knowledge Management (Finally) Extractive? – Fuller’S Argument Revisited In The Age Of Ai, Norman Mooradian

Faculty Research, Scholarly, and Creative Activity

Aim/Purpose The rise of modern artificial intelligence (AI), in particular, machine learning (ML), has provided new opportunities and directions for knowledge management (KM). A central question for the future of KM is whether it will be dominated by an automation strategy that replaces knowledge work or whether it will support a knowledge-enablement strategy that enhances knowledge work and uplifts knowledge workers. This paper addresses this question by re-examining and updating a critical argument against KM by the sociologist of science Steve Fuller (2002), who held that KM was extractive and exploitative from its origins. Background This paper re-examines Fuller’s argument …

Characterization Of Mycelium Biocomposites Under Simulated Weathering Conditions, Nicholas Schultz, Ajimahl Fazli, Sharmaine Piros, Yuritzi Barranco-Origel, Patricia Dela Cruz, Dr Yanika Schneider

Faculty Research, Scholarly, and Creative Activity

Expanded polystyrene (EPS) remains a popular packaging material despite environmental concerns such as pollution, difficulty to recycle, and toxicity to wildlife. The goal of this study is to evaluate the potential of an ecofriendly alternative to traditional EPS composed of a mycelium biocomposite grown from agricultural waste. In this material, the mycelium spores are incorporated into cellulosic waste, resulting in a structurally sound biocomposite completely enveloped by mycelium fibers. One of the main criteria for shipping applications is the ability of a material to withstand extreme weather conditions. Accordingly, this study focused on evaluating a commercially available mycelium material before …

Mitigating Risk: Predicting H5n1 Avian Influenza Spread With An Empirical Model Of Bird Movement, Fiona Mcduie, Cory T. Overton, Austen A. Lorenz, Elliott L. Matchett, Andrea L. Mott, Desmond A. Mackell, Joshua T. Ackerman, Susan E.W. De La Cruz, Vijay P. Patil, Diann J. Prosser, John Y. Takekawa, Dennis L. Orthmeyer, Maurice E. Pitesky, Samuel L. Díaz-Muñoz, Brock M. Riggs, Joseph Gendreau, Eric T. Reed, Mark J. Petrie, Chris K. Williams

Faculty Research, Scholarly, and Creative Activity

Understanding timing and distribution of virus spread is critical to global commercial and wildlife biosecurity management. A highly pathogenic avian influenza virus (HPAIv) global panzootic, affecting 600 bird and mammal species globally and over 83 million birds across North America (December 2023), poses a serious global threat to animals and public health. We combined a large, long-term waterfowl GPS tracking dataset (16 species) with on-ground disease surveillance data (county-level HPAIv detections) to create a novel empirical model that evaluated spatiotemporal exposure and predicted future spread and potential arrival of HPAIv via GPS tracked migratory waterfowl through 2022. Our model was …

Next Steps For Assessing Ocean Iron Fertilization For Marine Carbon Dioxide Removal, Ken O. Buesseler, Daniele Bianchi, Fei Chai, Jay T. Cullen, Margaret Estapa, Nicholas Hawco, Seth John, Dennis J. Mcgillicuddy, Paul J. Morris, Sara Nawaz, Nishioka, Anh Pham, Kilaparti Ramakrishna, David A. Siegel, Sarah R. Smith, Deborah Steinberg, Kendra A. Turk-Kubo, Benjamin S. Twining, Romany M. Webb

Faculty Research, Scholarly, and Creative Activity

There are many potential approaches to marine carbon dioxide removal (mCDR), of which ocean iron fertilization (OIF) has the longest history of study. However, OIF studies to date were not primarily designed to quantify the durability of carbon (C) storage, nor how wise OIF might be as an mCDR approach. To quantify C sequestration, we introduce a metric called the “centennial tonne,” defined as 1,000 kg of C isolated from atmospheric contact for on average at least 100 years. We present the activities needed to assess OIF from a scientific and technological perspective, and additionally, how it might be responsibly …

Resume Content Generation Using Llama 2 With Adapters, Navaneeth Sai Nidadavolu, William B. Andreopoulos

Faculty Research, Scholarly, and Creative Activity

This paper presents a novel approach to enhancing the Llama language model for generating customized resumes tailored to domain-specific job descriptions. Unlike traditional methods that rely heavily on extensive fine-tuning, we implement scalable adapter modules to minimize parameter adjustments. This approach preserves the model's inherent ability to generate coherent and contextually appropriate language across diverse tasks, ensuring that its general linguistic capabilities remain intact. Additionally, we employ a prompting strategy to dynamically create a diverse and comprehensive dataset, ensuring high relevance to various job roles. Using a dataset of 10,000 job descriptions and resumes, our approach resulted in a 20% …

Optimizing Field-Linked Simulations Of Dry Season Uptake And Monsoon Infiltration Within An Aspen-Mixed Conifer Forest, Raymond J. Hess

Master's Theses

Climate models forecast that headwater catchments in the western U.S. will undergo a reduction in snowpack, early season snowmelt, and increases in evapotranspiration. The resulting extended dry season will stress vegetation in mountainous watersheds throughout the Upper Colorado River Basin. We investigate infiltration patterns and root water uptake in response to dry season disturbances within the East River watershed in Colorado. To do this, we collected soil cores, measured matric potential and sap flow, and monitored tree xylem and soil for stable isotopes of water (2H, 18O) in two soil profiles to 90 cm depth (with three Engelmann spruce and …

Domain Switch On Sentiment Analysis Using Gradient Reversal Layer, Hemish Veeraboina

Master's Projects

Switching domains in sentiment analysis presents the challenge of transferring learned knowledge from one context to another without the need to label data. Traditional methods often struggle when dealing with differences in data distribution a problem known as the domain shift issue. To tackle this using Gradient Reversal Layers (GRL) has emerged as a solution for adapting to different domains in an unsupervised learning setting. This study introduces an enhancement to the standard GRL approach by incorporating a sigmoid function that gradually adjusts how intensely domain adaptation occurs during training. This upgraded GRL technique ensures controlled learning outcomes making it …

Emotion Detection Using Ensemble Learning, Priya Harika Yerapothu

Master's Projects

Emotion detection is gaining exponential necessity in today’s technological age. This research seeks to delve into ways conversational AI could be enhanced by integrating emotional intelligence using an ensemble learning approach. Traditional machine learning along with advanced neural network architectures are implemented to improve the understanding and intricacies of emotion detection from textual data. The dataset we use is GoEmotions dataset, annotated with 27 emotional labels, to conduct a detailed analysis of emotion recognition. Various machine learning models, such as HistGradientBoosting, LightGBM, CatBoost, and MLP, will be evaluated side by side with advanced models of Bidirectional Long Short-Term Memory (BiLSTM) …

Optimized Community Detection Across Distributed Heterogeneous Servers, Akash Narang

Master's Projects

The exploration of community detection is crucial across various fields, including marketing, and biological research. This area has evolved from non-overlapping communities to recognize nodes as part of multiple overlapping communities. Current research continues to uncover these dynamics. The main challenge is identifying overlapping communities in graphs with billions of nodes and edges. This paper aims to enhance methodologies for community detection in parallel for unprecedentedly large and complex networks. We introduce the HeteroNodesAdapter algorithm, which supports heterogeneous worker nodes and optimized load distribution in graph stream processing. Additionally, we propose the TailBalancedCommunitySize algorithm to find an optimum community size, …

Community Detection Using Deep Learning: Variational Graph Autoencoder Enhanced With Leiden And K-Truss Techniques, Jyotika Hariom Patil

Master's Projects

Community detection in networks is essential for understanding the complex structures of connected systems. Traditional deep learning (DL) methods such as Graph Neural Networks (GNNs) and Graph Convolutional Networks (GCNs) have shown promised results in supervised tasks, like classification, but often fail in unsupervised tasks like community detection because of the lack of labels. Self- supervised approaches where we integrate crucial community information offer a solution. This project seeks to explore DL methods for community detection, focusing specifically on using Graph Variational Autoencoders (VGAEs). While classical approaches can efficiently handle small to medium-sized networks, they typically struggle with larger-sized structures. …

Influence Maximization Using Triadic Closures, Communities, And Quotas, Matthew Fu

Master's Projects

Online social networks have exploded in popularity in the last decade. In addition, traditional advertising methods such as television advertising have greatly decreased. This allows companies to utilize viral marketing more effectively. With viral marketing, companies can spread information on a product to a social network by reaching out to a small group of early adopters, who will go on to inform the people around them of the product. The problem is selecting the early adopters that can maximize the spread of influence. The Influence Maximization (IM) problem is finding a social network’s most influential (early adopters) starting nodes, called …

Characterizing Nanopore Sequencing Artifacts With Deep Learning, David Zhou

Master's Projects

Oxford Nanopore sequencing is a revolutionary new technology for sequencing DNA molecules in long stretches. However, it has a significantly higher error rate than conventional short-read sequencing, resulting in numerous sequencing artifacts. These artifacts can be indistinguishable from low frequency somatic variants, which is a roadblock for cancer diagnosis using liquid biopsies. In this study, benchmarked human genome samples from Genome in a Bottle were used to create a dataset of labeled variants, including artifacts and true variants. Variant features, including sequence context, were used to train various deep learning models. The multi-input neural network combining sequence context features and …

Employing Large Language Models And Retrieval Augmented Generation For Enhanced Predictive Flexibility In Cancer Mortality Prediction, Mridang Kejriwal

Master's Projects

Today, cancer is a major health risk to thousands of people, and there are over a two-hundred different types of cancer. Luckily, over the past several years, the outcomes and survival rates have increased, all thanks to machine learning, specifically Recurrent Neural Networks (RNN) and Long Short-Term memory (LSTM) networks. However, the current prognostic models don’t allow healthcare professionals to adapt the variables to mimic all the different features of every type of cancer, resulting in a model that works but is not as accurate as it could be. This study explores improving the accuracy and adaptability of the current …

Temporal Dynamics In Diabetes Prediction: A Sensor-Driven Time-Series Exploration, Monica Meduri

Master's Projects

Diabetes is a lifelong illness that, if not detected or managed appropriately, turns into serious complications. Correct glucose forecasting is critical to ensuring timely interventions, thereby minimizing risks of hyperglycemia and hypoglycemia, and optimizing the management strategies of the disease. Classical machine learning models have been applied in the blood glucose forecasting problem for a long time, however, usage of transformer-based architectures is still scarce within the literature. Due to the self-attention mechanism, transformers can capture temporal relationships very effectively, which makes them suitable for time-series data. TFT is a novel framework proposed here to utilize time-series data from CGM …

Comparison Of Protein Structures Predicted By Genai Tools In A Zero-Shot Manner, Kruthi Shankar Rao

Master's Projects

Generative AI models have vast applications and one such critical application explored in this study is protein structure prediction. The 3D structures of proteins determine their function. Our study mainly focuses on using generative AI models such as ESMFold and ColabFold to predict and examine naturally occurring and mutated sequences. The workflow begins with collecting antimicrobial resistance (AMR) and toxin-antitoxin (TA) protein data. The sequences are applied over pretrained AI models to predict protein structures. Following this, models are fine-tuned with original and mutated target datasets. A comparison of models’ performances is done using metrics such as root mean square …

Artifacts In Low-Pass Whole Genome Sequencing, Nguyen Mai Anh Do

Master's Projects

Low-pass whole genome sequencing (LP-WGS) provides a cost-effective way to achieve broad genomic coverage, but it comes with the challenge of sequencing artifacts that can complicate accurate variant detection. To address this, we developed a bioinformatics pipeline using Nextflow. Starting with raw sequencing data, the pipeline performed variant calling using VarDict, with Genome in a Bottle (GIAB) high-confidence variants serving as the benchmark for variant validation. We explored machine learning approaches, testing classifiers such as AdaBoost, ExtraTrees, and RandomForest, to evaluate variant classification. Twenty-two features generated by VarDict were fed into Machine Learning pipeline, with AdaBoost standing out for its …

Detecting Crustose Coralline Algae (Cca) In Marine Photos Using Mask R-Cnn, Vrushali Harshwardhan Deshpande

Master's Projects

Coral reefs, made up of thousands of polyps - tiny sac-like marine invertebrates sea anemones and jellyfish, are important to marine ecosystems and prevent loss of life by acting as a natural barrier against storms, floods, and waves. These reefs support a wide range of species, many of which are underexplored and new species being discovered regularly. Crustose coralline algae (CCA) is one of the vital algal species that provides reef structure. Studying the abundance of CCA is important in helping marine biologists analyze coral reef health while understanding the impact of climate change on the marine lifeforms. This study …

Queer A.F.: Queer Educators In Affinity Family Personal-Professional Development, James Egisto Aguirre

Dissertations

Scholarship shows that affinity groups are spaces of support, learning, and healthy career development that are responsive to the needs of a particular marginalized community. The concept of heteroprofessionalism– the implicit or explicit pressure/s queer educators feel to fit within the proverbial cisgender/heterosexual (cishet) box–is but one of a myriad issues and pressures affect queer educators across the nation. This study brings queer educators from one school district together to unpack their experiences through the lens of heteroprofessionalism. Via queer theory, qualitative, written response data was collected and subsequently analyzed in three, half-day sessions offered in spring 2024. Thirty participants …

Artificial Intelligence Teamwork For Agricultural Information Service Delivery In A Changing World: A Paradigm Shift, Taiwo Bosede Ajayi Dr, Onaade Ojo Dr, Modupe Atinuke Otuyalo, Wosilat Omolara Oyeniyi, Oluwole Ibiyem Ogunyemi Dr, Rufus Dirinfo Dr

Library Philosophy and Practice (e-journal)

As the global agricultural landscape faces unprecedented challenges driven by climate change, population growth, and shifting consumer demands, there is a pressing need for innovative solutions to ensure food security and sustainable agricultural practices. This paper explores the transformative potential of Artificial Intelligence (AI) in reshaping how agricultural information is developed, disseminated, and utilized to enhance service delivery. AI-powered technologies, including machine learning, data analytics, and automation, are revolutionizing agriculture by providing real-time insights, optimizing resource allocation, and improving decision-making for farmers, policymakers, and stakeholders across the agricultural value chain. This research delves into the multifaceted applications of AI in …

Taking Environmental Responsibility Seriously: Academic Libraries, Ai, And Climate Impacts, Frank Houghton, Jennifer Moran Stritch, Lisa O'Rourke Scott

Library Philosophy and Practice (e-journal)

Generative AI is a disruptive technology that offers significant potential across many fields including healthcare, health education and academic libraries. However, although many concerns are routinely cited in relation to AI, very few of these address the issue of the increased power requirements inherent in AI training and inference. Climate change resulting from human factors has already resulted in increased global warming and climate variability. In this Anthropocene era the question must be asked how libraries and other organisations will mitigate the impacts of their increased AI use? To date assessments of sustainability and energy use in libraries have not …

The Evolving Role Of Libraries In The Fourth Industrial Revolution: Navigating Digital Transformation, Abdullahi Olayinka Isiaka, Abdulfatai Soliu, Biliamin Abiola Aremu, Benjamin Adebisi Bamidele, Saidu Saba-Jibril, Adelani Rotimi Ibitoye

Library Philosophy and Practice (e-journal)

Abstract

This article explores the transformative impact of the Fourth Industrial Revolution (4IR) on libraries and their pivotal role in navigating the challenges and opportunities brought forth by rapid technological advancements. Libraries, traditionally perceived as repositories of books and information, are undergoing a profound metamorphosis in the digital age. The 4IR, characterized by breakthroughs in Artificial Intelligence, the Internet of Things, and Data Analytics, demands a redefinition of the library’s purpose and services. The first section introduces the concept of the 4IR and its key technological advancements. Emphasis is placed on understanding the dynamic landscape of the 4IR and the …

The Role Of Nature As A Protective Factor In Father-Child Relationships, Sarah J. Barker

Master's Theses

The present study strived to understand how fathers spend time with their children outdoors and how this shared time together may positively influence their relationship within the Family-Based Nature Activities Theoretical Framework. The objectives of this thesis are to understand more about (a) Why fathers participate in outdoor activities with their children; and (b) How spending time outdoors with their children influences their relationship. Participants included 26 fathers (M=40.6 years old) and their children between the ages of 5-12 years old. All urban fathers resided on the West Coast, while rural fathers lived in the southeast United States. Participants were …

The Impact Of Daylight Saving Time Transitions On Domestic Violence Call Volume, Quynh-Nhu Pham

Master's Projects

Daylight Saving Time (DST) is a longstanding practice in many countries, involving the seasonal adjustment of clocks by one hour forward in the spring, and one hour backward in the fall. Although DST was initially introduced to promote energy conservation and maximize daylight hours, it has become a subject of debate, given its impact on physical and mental health, cognitive performance, and criminal behavior (Kountouris & Remoundou, 2014).

In 2022, Colorado enacted a law adopting year-round DST, contingent upon a federal law enabling states to maintain DST throughout the year as opposed to ST, like Hawaii and Arizona (Chasan, 2024). …

Addressing Equity Gaps In Stem: A Self-Study, Prabhjeet Kaur Brar

Dissertations

The Hispanic/Latinx population is increasing nationwide and in the state of California; however, the Hispanic/Latinx population remains underrepresented in STEM professions contributing to a lack of diversity in STEM. To increase the academic success of the Hispanic/Latinx student population in STEM majors, high leverage research-based teaching strategies through the lens of historically responsive literacy were applied and examined throughout this research. The purpose of this mixed-methods self-study was to examine the impact of research-based effective strategies/high leverage practices on Latinx students’ success rates in my introductory biology classrooms. The study focused on two biology course sections with a laboratory. Each …