Digital Commons Network^™

Artificial Intelligence For Better In-Game Nfl Performance, Christopher Mcmanus

Honors Theses

In this thesis I examined the use of AI modeling for the use in the modern-day NFL, both for improving in-game play calling, and creating better recovery plans for players all around the league. When finding articles detailing these models, I only focused on works involving the current day NFL, and models used widely around the league to this day. The literature detailed in this thesis mainly describes modeling used by Amazon Web Services (AWS, 2024, The NFL’s partner for all things analytics, and data modeling. My main objective for this literature review was to show the impact AI modeling …

The Few-Nexus: Using Soil To Grow Meaning And Relevance In Undergraduate General Education Earth Science Courses, Katherine Mccarville

National Collaborative for Research on Food, Energy, and Water Education (NC-FEW)

Soils are central to human survival, through their critical roles in regulating water supplies and providing the medium for most agricultural productivity. Even as fewer and fewer students know where their water and food come from, and where their wastes go, soils tend to be under-emphasized in Earth science general education courses. Combining a place-based focus on soils with the FEW-Nexus model provides an integrating context for concepts and information that students sometimes perceive as disconnected and irrelevant to them. This approach can transform the experiences and learning of undergraduate students in the Earth science general education curriculum.

“Smart Trap”: A Portable Device For Real-Time Mosquito Capturing And Classification Using Image-Based Analysis, Fahim Rahman

USF Tampa Graduate Theses and Dissertations

Capturing mosquitoes in real-time and taking high-quality images for classification with state-of-the-art methods is not only time-consuming but also expensive. Sometimes even carefully controlled environments and experimental setups fail to capture living mosquitoes. Catching live mosquitoes is necessary to be able to study aspects of their physiology and behavior that cannot be investigated by collections of resting mosquitoes and dead specimens, and to help estimate the local population numbers. My thesis introduces a “Smart Trap”, a small portable device that can attract mosquitoes in real-time, capture them, take high-quality images with dual cameras, and store those images in the cloud. …

The Sustainability Stones: Culturally Embedded Conservation Strategies And Their Vulnerability In Maupiti, French Polynesia, Russell Fielding, Fiona Gimenez

Honors College Faculty Publications

This paper explores culturally embedded conservation strategies through the lens of the traditional agroforestry and fisheries cycles in Maupiti, French Polynesia. By pairing certain breadfruit cultivars with specific fish species, the island’s community created a culinary system that regulates the seasonal consumption of marine resources, making the sustainable use of those resources more likely. While modern pressures such as reduced breadfruit diversity, competition with imported foods, and climate change have weakened these traditional practices, they remain an example of local ecological knowledge guiding conservation. The study highlights the threat of losing sustainable resource-use practices and biodiversity as both biodiversity and …

2024 Rmap Non-Residential Parcels Data Summary Report Silver Bow Creek/Butte Area Npl Site Bpsou, Environmental Standards, Inc., Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Examining Intersectional Queer Biases In Large Language Models: A Combined Statistical And Visual-Qualitative Approach For Quantification And Explanation, Huu Duong (Chip) Nguyen

Computer Science Senior Theses

Despite significant advancements in research on (intersectional) social biases in Large Language Models (LLMs), intersectional biases affecting subgroups within the LGBTQ+ community remain critically understudied. Existing bias detection methodologies often prioritize quantification but lack depth in explaining the specific stereotypes/biases that shape evaluation metrics. To address these gaps, this study proposes a combined statistical and visual-qualitative approach to quantify and identify persistent intersectional queer biases in five recent, state-of-the-art LLMs through a downstream story generation task. Findings from analysis uncover substantial evidence of stereotypes that perpetuate harmful, reductive narratives against intersectionally marginalized groups within the LGBTQ+ community. To promote public …

Precision Phenotyping For Curating Research Cohorts Of Patients With Unexplained Post-Acute Sequelae Of Covid-19, Alaleh Azhir, Jonas Hügel, Jiazi Tian, Jingya Cheng, Ingrid V Bassett, Douglas S Bell, Elmer V Bernstam, Maha R Farhat, Darren W Henderson, Emily S Lau, Michele Morris, Yevgeniy R Semenov, Virginia A Triant, Shyam Visweswaran, Zachary H Strasser, Jeffrey G Klann, Shawn N Murphy, Hossein Estiri

Faculty, Staff and Student Publications

BACKGROUND: Scalable identification of patients with post-acute sequelae of COVID-19 (PASC) is challenging due to a lack of reproducible precision phenotyping algorithms, which has led to suboptimal accuracy, demographic biases, and underestimation of the PASC.

METHODS: In a retrospective case-control study, we developed a precision phenotyping algorithm for identifying cohorts of patients with PASC. We used longitudinal electronic health records data from over 295,000 patients from 14 hospitals and 20 community health centers in Massachusetts. The algorithm employs an attention mechanism to simultaneously exclude sequelae that prior conditions can explain and include infection-associated chronic conditions. We performed independent chart reviews …

Artificial Intelligence And Communication Technologies In Academia: Faculty Perceptions And The Adoption Of Generative Ai, Aya Shata, Kendall Hartley

Hank Greenspun School of Journalism and Media Studies Faculty Research

Artificial intelligence (AI) is ushering in an era of potential transformation in various fields, especially in educational communication technologies, with tools like ChatGPT and other generative AI (GenAI) applications. This rapid proliferation and adoption of GenAI tools have sparked significant interest and concern among college professors, who are dealing with evolving dynamics in digital communication within the class-room. Yet, the effect and implications of GenAI in education remain understudied. Therefore, this study employs the Technology Acceptance Model (TAM) and the Social Cognitive Theory (SCT) as theoretical frameworks to explore higher education faculty’s perceptions, attitudes, usage, and motivations, as the underlying …

Predicting Freshwater Spring Distribution Using Maxent Modeling: A Case Study In Groundwater Management Area 9 (Gma-9), Texas, Zayed Mallick

USF Tampa Graduate Theses and Dissertations

Freshwater springs are one of the most vital groundwater sources and they have been a reliable water source for mining, irrigation, drinking, and farming, particularly in hot and arid regions like Groundwater Management Area-9 (GMA-9), Texas. However, excessive groundwater extraction, climate change, and environmental degradation have created tremendous stress on the sustainability of freshwater springs and as a result, they might not be able to meet the future water demand. This study uses the Maximum Entropy (MaxEnt) model to predict the distribution of springs in GMA-9 and to identify the key topographic and climatic factors influencing their occurrence. This study …

Accretion And Accumulation Of Mangrove Soils In Clam Bay, Naples, Fl: The Impact Of Hydrological Alterations And Sea-Level Rise, Matthew C. Fairchild

USF Tampa Graduate Theses and Dissertations

The ability of mangrove soils to accrete at a rate that keeps up with the rate of sea-level rise (SLR) is widely debated, especially for soils impacted by variations in influxes of nutrients and alterations in natural flows of water from surrounding urban areas. This study aimed to evaluate the influence of SLR on mangrove soils in Clam Bay (Naples, Florida, USA), which has an extensive system of mangroves that have faced increasing human pressure in recent decades as well as SLR. Cores were collected from two different sites within Clam Bay to identify differences in soil accretion, mass accumulation, …

Salmon As An Ecological Pathway Of Contaminants Into Alaskan Food Webs, Miranda Brohman, Gretchen Roffler, Dimitri G. Giarikos, David Kerstetter, Amy C. Hirons

SECLER Data

Salmon are important fish taxa for humans and animals in hemiboreal and subarctic ecosystems. Trace elements and their marine food web bioaccumulation raises biomagnification and potential human health risk concerns. Sixteen trace element concentrations and their health risk assessments were determined in seven different tissues of two Southeast Alaska salmon species (chum, Oncorhynchus keta and pink, Oncorhynchus gorbuscha). Chum tissues had overall higher trace element concentrations compared to pink, which may be attributed to a difference of diets, generally longer-lived and spending more time in the open ocean. All kidney and liver samples exceeded the tolerable daily intake for …

Characterizing Rainfall Variability Within A Series Of Storms Over Northern California In February 2017, Parker Jan Malek

Dissertations and Theses

In February 2017, a series of storms with associated atmospheric rivers (ARs) made landfall in the US state of California, dropping large amounts of precipitation over the Sierra Nevada Mountains and their western foothills. The rainfall from these ARs, long, narrow bands of water vapor that transport large amounts of water vapor from the tropics to the mid-latitudes, instigated the near-failure of the Oroville Dam located at the southeastern edge of the Feather watershed outside the city of Oroville in the state's Central Valley. This case study provides a synoptic and mesoscale diagnosis of the drivers of rainfall pulses that …

Next Arrival And Destination Prediction Via Spatiotemporal Embedding With Urban Geography And Human Mobility Data, Pengjiang Li, Zaitian Wang, Xinhao Zhang, Pengfei Wang, Kunpeng Liu

Computer Science Faculty Publications and Presentations

With the development of transportation networks, countless trajectory data are accumulated, and understanding human mobility from traffic data could be helpful for smart cities, urban computing, and urban planning. Extracting valuable insights from traffic data, such as taxi trajectories, can significantly improve residents’ daily lives. There are many studies on spatiotemporal data mining. As we know, arrival prediction or regional function detection encompasses important tasks for traffic management and urban planning. However, trajectory data are often mutilated because of personal privacy and hardware limitations, i.e., we usually can only obtain partial trajectory information. In this paper, we develop an embedding …

Enhanced Vapour Detection Through Electrospun Metal-Oxide Nanofibers, Sri Varshini K Ms

Theses and Dissertations

The objective of this work is to fabricate metal oxide-based nanofibers, which helps in monitoring indoor air quality, which is deteriorating due to VOCs like Formaldehyde, Toluene, and Ammonia, commonly found in paints, plywood, and adhesives. Prolonged exposure to these VOCs can affect the respiratory and nervous system. They are classified as carcinogens by the IARC.

Based on the analysis, this work was framed to deposit Fe2O3, NiO, and ZnO/Fe2O3 as well ZnO/NiO and Fe2O3/NiO nanofibers on the glass substrate through horizontal electrospinning method. The obtained nanofibers are vacuum annealed at 50 ℃ for 30 mins to remove the water …

Transfer Learning In Junction With A Light Use Efficiency Model For Estimating Grassland Gross Primary Production, Ruiyang Yu, Yunjun Yao, Qingxin Tang, Xueyi Zhang, Changliang Shao, Joshua B. Fisher, Jiquan Chen, Xiaotong Zhang, Yufu Li, Jia Xu, Lu Liu, Zijing Xie, Jing Ning, Jiahui Fan, Luna Zhang

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

It is significant to simulate grassland gross primary production (GPP) to understand the terrestrial carbon budget over Inner Mongolia (IMG), China. Nevertheless, there is not sufficient in situ GPP data over this region. In this study, we proposed a novel model-based transfer learning (MTL) approach with generative adversarial networks-long short-term memory (GAN-LSTM) and light use efficiency (LUE) models to derive grassland GPP over IMG, China. We first used 25 grassland eddy covariance sites over the conterminous United States to establish the GAN-LSTM model and then fine-tuned it with six sites over IMG to estimate water constraints that were embedded into …

Evaluating The Meditation Practices And Barriers To Adopting Mindful Medicine Among Physicians, Tiffany Champagne-Langabeer, Chelsea G Ratcliff, Christine Bakos-Block, Francine Vega, Marylou Cardenas-Turanzas, Aila Malik, Radha Korupolu

Faculty, Staff and Student Publications

Background: Chronic pain affects over 25% of U.S. adults and is a leading cause of disability. Mindfulness meditation (MM) is a nonpharmacologic approach to manage pain and improve well-being. Despite mounting evidence supporting its efficacy, MM remains underutilized in medical practice. Understanding physicians' engagement with MM and the barriers they face can inform strategies for integration into clinical care. This study assessed physicians' attitudes toward MM, including barriers to practice and their likelihood of recommending it to patients.

Methods: A cross-sectional survey of U.S. physicians was conducted from April to July 2024. Participants provided information on demographics, health struggles, and …

A Comparison Of Unconventional Microwave And Ultrasound-Assisted Extraction Methods Used For Flavonoids, Istiqomah Rahmawati, Daffa Hafiziaulhaq Azizi, Jihan Nafila Wibowo, Muhammad Reza, Boy Arief Fachri, Bekti Palupi, Meta Fitri Rizkiana, Helda Wika Amini, Ifan Ramadana, Felix Arie Setiawan

Makara Journal of Science

Cocoa pods (Theobroma cacao L.) are a rich source of flavonoids, which are natural antioxidants known for their health benefits. This study investigated the use of microwave-assisted extraction (MAE) and ultrasound-assisted ex-traction (UAE) to extract the maximum flavonoids and antioxidants from cocoa pods. MAE and UAE are efficient and sustainable methods for extracting bioactive compounds like flavonoids and antioxidants from cocoa pods, offer-ing faster extraction, reduced solvent use, and better compound preservation compared to conventional methods. These technologies unlock the untapped potential of cocoa pods for applications in food, cosmetics, and pharmaceuti-cals. The effects of extraction time (2–10 min), microwave …

Overexpression And Biophysical And Functional Characterization Of A Recombinant Fgf21, Phuc Phan, Jason Hoang, Thallapuranam Krishnaswamy Suresh Kumar

Chemistry & Biochemistry Faculty Publications and Presentations

Fibroblast growth factor 21 (FGF21) is an endocrine FGF that plays a vital role in regulating essential metabolic pathways. FGF21 increases glucose uptake by cells, promotes fatty acid oxidation, reduces blood glucose levels, and alleviates metabolic diseases. However, detailed studies on its stability and biophysical characteristics have not been reported. Herein, we present the overexpression, biophysical characterization, and metabolic activity of a soluble recombinant FGF21 (rFGF21). The far-UV circular dichroism spectra of rFGF21 show a negative trough at 215 nm, indicating that the protein's backbone predominantly adopts a 13 sheet conformation. rFGF21 shows intrinsic tyrosine fluorescence at 305 nm. Thermal …

Challenges In Artisanal Small-Scale Gold Mining: Perspectives And Transformations To Sustainability Along Br-163 In Brazil, Carlos Henrique Xavier Araujo, Irfan Ullah, Giorgio De Tomi

Journal of Sustainable Mining

Artisanal Small-scale Gold Mining (ASGM) is a sector beset with unique and complex challenges. Recent literature highlights the growing acknowledgment of the critical need for reforms in how the ASGM industry interacts with communities and the environment. Discussions about sustainable transformations go beyond theoretical and conceptual borders, attempting to understand how local transformative events might reflect global developments. Thus, the goal of this article is to give an analysis from the perspective of the actors participating in artisanal gold mining activities. A survey was carried out along BR-163, which runs from Sinop (Mato Grosso) to Santarém (Pará). Fifty-five (55) interviews …

Comprehensive Review On The Application Of Bio-Immunoinformatics In The Development Of Highly Ef-Fective New Candidate Vaccines Against Tuberculosis, Ahyar Ahmad, Andriansjah Rukmana, Miski A. Khairinisa, Dian A. E. Pitaloka, Rosana Agus, Rusdina B. Ladju, Tarwadi Ahmad, Astutiati Nurhasanah, Carina C. D. Joe, Muhammad N. Massi, Harningsih Karim, Irda Handayani, Siti Roszilawati Binti Ramli

Karbala International Journal of Modern Science

Tuberculosis (TB) remains a significant public health challenge worldwide. Currently, Bacillus Calmette-Guerin (BCG) is the only vaccine available for TB prophylaxis. However, the efficacy of the BCG vaccine against adult pulmonary TB is considered inconsistent. This condition encourages researchers to look for more effective options, such as subunit vaccines. This condition requires the development of a more effective subunit vaccine to protect active TB in productive and adult ages. There is an urgent need for more effective vaccines, as the Bacillus Calmette-Guérin (BCG) vaccine currently available has inconsistent efficacy and is only partially effective in adults. Bio-immunoinformatics, an interdisciplinary field …

Transcriptional Profiles Reveal Physiological Mechanisms For Compensation During A Simulated Marine Heatwave In Yellowtail Kingfish (Seriola Lalandi), Sharon E. Hook, Ryan J. Farr, Jenny Su, Alistair J. Hobday, Catherine Wingate, Lindsey Woolley, Luke Pilmer

Fisheries Research Articles

Background

Changing ocean temperatures are already causing declines in populations of marine organisms. Predicting the capacity of organisms to adjust to the pressures posed by climate change is a topic of much current research effort, particularly for species we farm or harvest. To explore one measure of phenotypic plasticity, the physiological compensations in response to heat stress as might be experienced in a marine heatwave, we exposed Yellowtail Kingfish (Seriola lalandi) to sublethal heat stress, and used the transcriptome in gill and muscle, benchmarked against heat shock proteins and oxidative stress indicators, to characterise the acute heat stress …

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Quarterly Operations And Maintenance Report Butte Treatment Lagoons (Btl) System – Third Quarter 2024 (Dated December 23, 2024), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Predicting Precipitation And Ndvi Utilization Of The Multi-Level Linear Mixed-Effects Model And The Ca-Markov Simulation Model, Fatima Belhaj, Hlila Rachid, Ouallali Abdessalam, Aqil Tariq, Belkendil Abdeldjalil, Beroho Mohamed, Hassan Alzahrani, Hajra Mustafa, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

The current work intends to reconstruct the spatiotemporal evolution of precipitation and the Normalized Differentiate Vegetation Index (NDVI) in the Loukkos watershed and provide scenarios for their recent and future evolution, therefore determining the degree of association. We conducted a study on the time series data of precipitation and NDVI from 1999 to 2019. The NDVI prediction is conducted using the CA-Markov model and the linear mixed-effects multi-level model (LME) with precipitation data from 2019 to 2040. The CA-Markov model was employed to predict the vegetation indices for 2029 and 2040 using 1999, 2009, and 2019 data. The model simulates …

Leveraging Large Language Models For Knowledge-Free Weak Supervision In Clinical Natural Language Processing, Enshuo Hsu, Kirk Roberts

Faculty, Staff and Student Publications

The performance of deep learning-based natural language processing systems is based on large amounts of labeled training data which, in the clinical domain, are not easily available or affordable. Weak supervision and in-context learning offer partial solutions to this issue, particularly using large language models (LLMs), but their performance still trails traditional supervised methods with moderate amounts of gold-standard data. In particular, inferencing with LLMs is computationally heavy. We propose an approach leveraging fine-tuning LLMs and weak supervision with virtually no domain knowledge that still achieves consistently dominant performance. Using a prompt-based approach, the LLM is used to generate weakly-labeled …

Artificial Intelligence In Decision-Making: Literature Review, Najm A. Kh. Alhatimi Aleessawi, Leila Djaghrouri

Journal of the Association of Arab Universities for Research in Higher Education مجلة اتحاد الجامعات العربية للبحوث في التعليم العالي

In the fast-changing world of artificial intelligence (AI), the relationship between technology and decision-making has become a central area of study. Over the past five years, numerous papers have been published examining how AI methods are applied to decision-making processes across various industries. This article aims to highlight the key potential of artificial intelligence to enhance decision-making. It does so by systematically reviewing the literature on the role of AI in improving decision-making, particularly studies published between 2020 and 2024. The review consolidates the main findings from articles in renowned databases such as Google Scholar, Scopus, and IEEE Xplore, offering …

Unraveling Genetic Links Between Diabetes And Heart Failure-A Machine Learning Approach, Sunakhi Sahoo, Marzieh Ayati

Research Symposium

Background: Diabetic heart failure (DHF) is defined as a chronic and progressive disease which is associated with both diabetes and heart failure (HF). Even though there have been many developments in the knowledge of these diseases, there is still much to learn about the genetic crossovers between the two. In this study, we identified genes that are associated with diabetic heart failure and heart failure by using gene expression data from patients with DHF, HF, and a control group of patients who died of natural causes. We sought to identify genes that had altered expression levels which could possibly play …

Visible-Light-Driven Catalytic Dehalogenation Of Trichloroacetic Acid And Α-Halocarbonyl Compounds: Multiple Roles Of Copper, Abigail J. Thillman, Erin C. Kill, Alexander N. Erickson, Dian Wang

Chemistry Faculty Research and Publications

Herein, we report the reaction development and mechanistic studies of visible-light-driven Cu-catalyzed dechlorination of trichloroacetic acid for the highly selective formation of monochloroacetic acid. Visible-light-driven transition metal catalysis via an inner-sphere pathway features the dual roles of transition metal species in photoexcitation and substrate activation steps, and a detailed mechanistic understanding of their roles is crucial for the further development of light-driven catalysis. This catalytic method, which features environmentally desired ascorbic acid as the hydrogen atom source and water/ethanol as the solvent, can be further applied to the dehalogenation of a variety of halocarboxylic acids and amides. Spectroscopic, X-ray crystallographic, …

Editorial: Machine Learning Advancements In Pharmacology: Transforming Drug Discovery And Healthcare, Moom Rahman Roosan, Ramgopal Mettu

Pharmacy Faculty Articles and Research

"In recent years, the integration of machine learning (ML) into pharmacology has revolutionized how we approach drug discovery, disease modeling, and therapeutic development. By leveraging vast datasets and computational power, ML has enabled researchers to uncover patterns, predict outcomes, and accelerate drug development processes that were previously unimaginable. This Research Topic on 'Machine Learning Advancements in Pharmacology' features five impactful studies that highlight the diverse applications and potential of ML in this field. These contributions, encompassing original research and a systematic review, exemplify the transformative role of ML in addressing some of the most pressing challenges in pharmacology."

Designing Accessible Ui/Ux For Epileptic Patients: A Scalable Solution For Music Therapy Delivery, Amethyst G.H. Mckenzie

Computer Science Senior Theses

How can we design an accessible, scalable UI/UX system tailored to the cognitive, visual, and motor impairments of epileptic patients, that ensures safe and effective interactions with music therapy applications? This research explores the intersection of accessibility, user-centred design, and digital health, using an iterative design process to develop and refine the SONATA app—a clinically deployable music therapy platform.

Through two prototype iterations, usability testing, and quantitative event logging, this study compares the effectiveness of structured versus flexible navigation in improving user experience. Key findings reveal that structured navigation reduces unintended detours, while progressive disclosure techniques enhance instructional clarity. Additionally, …

Discounting Effect Size When Borrowing External Data In Clinical Studies, Zhuanzhuan Ma, Chul Ahn, Bin Wang, Xuefeng Li

Research Symposium

Background: When borrowing information from external data to augment a current trial, many available methods discount the sample size but retain the effect size from previous studies. Discounting the sample size is just one way to discount the prior information. It may not be appropriate if the underlying assumption of unbiased treatment effect does not hold, for example, when the treatment effect in the historical study is likely higher than the one expected in the current trial.

Methods: To tackle this potential issue, we study some methods to shrink the effect size from previous studies assuming that the prior effect …