Digital Commons Network^™

Vibrations Of Tapered Beam Via The Exterior Matrix Method, Simranjit Kaur

Student Theses and Dissertations

Cell phone towers, utility poles, and traffic signal poles all use hollow, tapered beams as their main structural element. Because these structures are tall and exposed to wind forces, understanding their vibration behavior is important for ensuring stability and safety. We will use the Exterior Matrix Method to analyse a single beam, which can be used to analyse compound structures involving tapered beams. First, we find the system of four equations satisfied by the tapered beam, which can be converted to a 4 x 4 matrix. Then we find the exterior matrix, which is a 6 x 6 matrix, corresponding …

The Ecotoxicological Implications Of Switching From Fluorescent To Light Emitting Diode Lighting For Zooplankton Culturing And Whole Effluent Toxicity Testing, Orithea Z. Regn

Student Theses and Dissertations

In the global transition toward light emitting diode (LED) lighting, an understudied area is the impact on the culturing and testing of Whole Effluent Toxicity (WET) testing organisms, more specifically, the zooplankton species. Without comparison to the current lighting used for culturing and testing, it is unknown if there will be an impact on performance, which could affect effluent, regulatory, and product safety decisions. This dissertation investigated if culturing and reference toxicity testing using sodium chloride for Ceriodaphnia dubia, Daphnia magna, and D. pulex under LED lighting was comparable to fluorescent. Comparisons were made between two laboratories and by season, …

American Sign Language Recognition And Analysis Using Deep Learning, Saurabh Kumar Soni

Master’s Dissertations

In this work I build a system that recognizes isolated American Sign Language (ASL) words, and I use it to ask one fairly direct question: when training data is scarce, is it better to look at the video pixels or at the geometry of the signer’s body? To find out, I train two very different models on exactly the same clips. The first is appearance-based. Every frame is run through standard preprocessing and a ResNet50 backbone pre-trained on ImageNet, which turns it into a 2048-dimensional feature vector, and a Bidirectional LSTM then reads that sequence over time. The second model …

An Empirical Study Of Rlvr Fine-Tuning For Mathematical Problem Solving In Llms, Rashmi Konnur

Master’s Dissertations

Large language models have shown immense improvement in coding and math performances thanks to reinforcement learning boosted algorithms. However, its true impact on broadening the reasoning and analytical capacities of an LLM is still contended. In this dissertation, we outline the foundations of Large Language Models, and delve into Reinforcement Learning with Verifiable Rewards (RLVR). We discuss various strategies to efficiently manipulate memory during a fine tuning update. We finally perform RLVR fine-tuning techniques on different models with varied use cases and compare their performances, which corroborate the efficiency of RLVR.

Development Of A Coupled Hydrological-Nitrogen Modeling Framework For Urban Stormwater Pond Analysis, Tione Grant

USF Tampa Graduate Theses and Dissertations

Urbanization impacts the hydrological and biogeochemical processes that regulate water quality in downstream ecosystems, leading to increased stormwater volume and nitrogen loads in receiving aquatic environments. Although stormwater ponds are designed as simple hydraulic storage basins, they function more like managed ecosystems within urban drainage systems, offering both hydraulic attenuation and passive nutrient treatment. However, nitrogen removal efficiency varies significantly and depends on interactions between hydrological and biogeochemical factors. This thesis details the development, calibration, validation, and sensitivity analysis of a coupled hydrological-nitrogen model framework for Aaran’s Pond, an urban stormwater pond in Hillsborough County, Florida.

A process-based water budget …

Development And Evaluation Of The East Florida Coastal Ocean Model (Efcom), Orion B. Scharton-Witmer

USF Tampa Graduate Theses and Dissertations

Florida’s Atlantic coast has abundant resources in beaches, state parks, aquatic preserves, and wildlife refuges as well as densely populated coastal cities in low lying areas that are all subjected to natural disaster threats from the oceans. There is an urgent need for a high-resolution coastal ocean circulation model for this region. Based on the application of the Finite Volume Community Ocean Model (FVCOM), an East Florida Coastal Ocean Model (EFCOM) is developed, downscaling from the deep ocean, across the continental shelf, and into the estuaries. It employs an unstructured grid with horizontal resolution varying from 3 kilometers at the …

Boiling Flow Estimation For Aero-Optic Phase Screen Generation, Jeffrey W. Utley, Gregery T. Buzzard, Charles A. Bouman, Matthew R. Kemnetz

Faculty Publications

Aero-optic effects due to turbulence can reduce the effectiveness of transmitting light waves to a distant target. Methods to compensate for turbulence typically rely on realistic turbulence data, which can be generated by i) experiment, ii) high-fidelity computational fluid dynamics (CFD), iii) low-fidelity CFD, and iv) autoregressive methods. However, each of these methods has significant drawbacks, including monetary and/or computational expense, limited quantity, inaccurate statistics, and overall complexity. By contrast, the boiling flow algorithm is a simple, computationally efficient model that can generate atmospheric phase screen data with only a handful of parameters. However, boiling flow has not been widely …

Some New Oscillatory Behavior Of Higher-Order Elliptic Partial Differential Equations, S. Priyadharshini, V. Sadhasivam, Samrajesh Mault, K. K. Viswanathan

Mansoura Engineering Journal

The main objective of this study is to investigate the new adequate conditions for oscillation of higher-order elliptic partial differential equations by using the Riccati transformation and integral average method. The Riccati transformation converts a nonlinear first order Riccati differential equation into a second order linear ordinary differential equation, enabling solution via standard linear methods followed by inversion. Our plan of action is to reduce the multidimensional problem to an ordinary differential problem by using Jensen's inequality. Elliptic partial differential equations are used in almost every field of mathematics and physics, including Lie theory, geometry, and harmonic analysis. An elliptic …

Knowledge, Attitude, And Practice Regarding Vitamin D Among Adults In Western Libya: Assessment And Socio-Demographic Influences, Abdounasser Albasher Omar, Kawther Adaila, Mofida M. Alfaid, Abdurrahman M Sweidan, Ruqayah Kasheem, Samia Emhemmed Abadi, Abdulnabi Ali Abushita, Hafsa A. Alemam

Al-Bahir

Vitamin D deficiency is a widespread public health concern, necessitating a clear understanding of knowledge, attitudes, and practices (KAP) among populations. Therefore, this study was conducted to assess Libyan citizens' knowledge, attitude, and practice (KAP) regarding vitamin D in the western region of Libya. This study was carried out between June and September of 2021. A questionnaire was distributed across the study area and the complete responses were 314, with 62.7% were females and 37.3% were males.  The scores were calculated as percentages and statistically tested. Additionally, the impact of some socio-demographic factors (age, gender, education level, job, and salary) …

Production, Purification, And Crystallization Of The Recombinant Her2 Tyrosine Kinase Domain (Her2-Tkd), Edanur Topalan, Hali̇li̇brahi̇m Çi̇ftçi̇, Hasan Demi̇rci̇

Turkish Journal of Chemistry

The human epidermal growth factor receptor 2 tyrosine kinase domain (HER2-TKD) is an important therapeutic target in oncology. In this study, we developed a practical and cost-effective approach for producing soluble recombinant HER2-TKD in Escherichia coli as a basis for structure-based drug discovery. The gene encoding HER2-TKD was cloned into a pET28a(+) expression vector and expressed in E. coli. Since the protein was initially obtained as inclusion bodies, solubilization with 1.5% sarcosyl was applied to recover it in soluble form. The purified protein was obtained through size-exclusion chromatography, followed by tag removal using reverse affinity purification. Crystallization trials were performed …

Quantum Engineered Mxene–Graphene–Plasmonic Nanocomposites For Next-Generation Transparent And Flexible Space Photovoltaics, Arash Vaghef-Koodehi

Turkish Journal of Chemistry

This study presents a quantum‑engineered, tricomponent heterostructure comprising Ti3C2T MXene quantum dots (2–5 nm), single‑layer graphene, and plasmonic gold nanoparticles (15 ± 3 nm) uniformly embedded within electrospun polyacrylonitrile nanofibers. This integrated architecture demonstrates a remarkable combination of optical transparency (89.3 ± 1.1%) and power conversion efficiency (19.7 ± 0.4%) under AM0 solar illumination, representing 340% enhancement over state‑of‑the‑art transparent photovoltaic devices. A multiscale computational framework, bridging density functional theory and device‑level drift-diffusion modeling, identifies optimal interlayer spacing (3.4 ± 0.1 Å) as the key to achieving 89.3% charge‑transfer efficiency. Concurrently, localized surface plasmon resonances at 532 nm generate electromagnetic …

Efficient Heterogeneous Photo-Fenton Degradation Of Azo Dyes Using The Nanocomposite Mgfe2o4/Mos2, Zahra Zeinali, Leila Ershadi Afshar, Naz Chaibakhsh, Farnaz Isapour

Turkish Journal of Chemistry

In the present work, a facile hydrothermal route was employed to synthesize the nanocomposite MgFe2O4/MoS2, which acted as a heterogeneous photo-Fenton catalyst for the degradation of a synthetic diazo dye, Acid Blue 113 (AB113). The nanocatalyst produced underwent analysis using multiple characterization techniques. The parameters influencing the oxidative reaction were statistically modeled and optimized using response surface methodology. Optimal degradation efficiency for AB113 (94.92%) was attained at pH 8.79 using 10 mg of MgFe2O4/MoS2 nanocatalyst, 1.6 mL of H2O2, and a reaction duration of 27 min. The synergistic effect resulting from the formation of electron-hole pairs renders the combined photocatalysis …

Electrochemical Biosensing Of Alpha-Fetoprotein Based On Carboxylated Multi-Walled Nanotube-Polyazur A (In Des)-Gold Nanoparticles, Merve Yilmaz Çilçar, Meli̇ke Bi̇lgi̇ Kamaç

Turkish Journal of Chemistry

AFP, a cancer biomarker, is monitored during fetal development and in the serum of pregnant women. Sensitive and rapid monitoring of AFP is crucial for effective management. In this study, screen-printed carbon electrodes (SPCEs) modified with multi-walled carbon nanotubes (MWCNT-COOH), polyAzur A (PAA), which was prepared in a deep eutectic solution (DES), and gold nanoparticles (AuNP) were fabricated. AFP biosensors were developed for practical, sensitive, low-cost, and rapid detection of AFP. Optimizations of nanostructures (MWCNT-COOH, AuNP) and polymers (PAADES) were performed. The MWCNT-COOH, PAADES, and AuNP-modified SPCEs were characterized by FE-SEM-EDX, FTIR, and XRD techniques. The amounts of 6-MOH, APTES, …

[H]-Mediated Enhancement Of The Fenton Reaction Over A Pd/Uio-66(Zr)-F4 Catalyst, Juanhong Li, Suqin Wang, Xin Liu, Feng Liu

Turkish Journal of Chemistry

A [H]-accelerated catalytic Fenton system was developed using Pd/UiO-66(Zr)-F4 as the catalyst. This system enabled the regeneration of Fe²⁺ and facilitated the continuous generation of both ·OH and 1O2 through [H]-mediated electron transfer at ambient temperature and pressure. Under the conditions of 0.2 g L−1 catalyst (Pd loading 0.516 wt%), 25 μM Fe2+, 60 mL min−1 H2 flow (as the [H] source), 20 mM H2O2, and pH 3, approximately 89% of carbamazepine (initial concentration 20 mg L−1) was degraded within 3 h using trace iron. However, the catalytic activity of Pd/UiO-66(Zr)-F4 gradually declined from 89% to 53% over six reaction …

Alcohol-Based Microextraction Of Rhodamine 6g From Soft Drink, Food, And Cosmetic Samples, Mustafa Soylak, Esra Yamaner, Özgür Özalp

Turkish Journal of Chemistry

By using alcohol-based solvent extraction without tetrahydrofuran, a liquid–liquid microextraction technique was developed for the separation–enrichment of trace levels of Rhodamine 6G from complex matrices, including soft drinks, food, cosmetics, hygiene products, and natural waters. Numerous experimental parameters were tuned, including pH, alcohol volume, ultrasonication time, and sample and eluent volume. The enrichment factor (EF), limit of detection (LOD), and limit of quantification (LOQ) were used to assess the analytical performance of the suggested approach. The LOD and LOQ were 6.92 ng mL−1 and 23 ng mL−1, respectively, and the EF was 14. Through the use of the standard addition …

A Nonenzymatic Electrochemical Glucose Sensor Depending On A Ninps/Co3o4/Functionalized Graphene Oxide-Modified Working Electrode, Sümeyra Pekmez, Muhammet Güler

Turkish Journal of Chemistry

In the present research, the aim was to develop a novel electrochemical enzyme-free glucose sensor dependent upon a nickel nanoparticles (NiNPs)/cobalt (II, III) oxide (Co3O4)/carboxylated graphene oxide (GO-COOH)-modified glassy carbon (GC) electrode. The electrocatalytic performance of the electrode was tested using various electrochemical methods such as amperometry and cyclic voltammetry (CV). The NiNPs@Co3O4/GO-COOH/GC electrode showed noticeably superior electrocatalytic behavior for glucose oxidation in 0.1 M NaOH media, ascribed to the good synergistic impact between NiNPs, Co3O4, and GO-COOH. The amperometric response of the NiNPs@Co3O4/GO-COOH/GC electrode to glucose exhibited two linear determination ranges at +0.55 V potential. The first one was …

Synthesis Of Two Hofmann-Type-Like Clathrates, Characterizations, And Investigation Of Their Structures, Spectroscopic And Theoretical Properties, Zari̇fe Si̇bel Şahi̇n, Zeki̇ Kartal

Turkish Journal of Chemistry

This study concerns two Hofmann-type-like clathrates using 4-aminopyridine (4AP) as ligands and the transition metal atoms copper (Cu) and zinc (Zn). These clathrates have the structural features of heteronuclear tetracyanonickelate(II) and contain H2O and 4AP molecules as guest molecules, respectively. These two clathrates were characterized by infrared spectroscopy (IR), elemental analysis, and single crystal X-ray diffraction (SC-XRD) techniques. Based on elemental and spectral data, the structural formulae describing these clathrates were found to be [Cu(II)(4AP)4Ni(μ-CN)2(CN)2]·H2O (1) and [Zn(II)(4AP)4Ni(μ-CN)2(CN)2]·(4AP) (2). In addition, the values of some optical, electronic, and thermochemical properties of the two obtained clathrates calculated with the Gaussian 03 …

Efficient Multimodal Foundation Model Tuning For Hallucination Mitigation, Fei Zhao

ETDs from 2020-2029

Over the past few years, multimodal foundation models have achieved remarkable progress in perception and understanding. However, two challenges limit their reliability: (1) dependence on offline training, which in most real-world settings requires large volumes of labeled data and, as a result, hinders the model’s ability to adapt to new data or domains; (2) weak cross-modal grounding, which often leads to hallucinated content generation, producing descriptions that are linguistically fluent but inconsistent with the input visual evidence. This dissertation frames hallucination mitigation as an outcome of transitioning from fixed learning (static, offline fine-tuning) to adaptive, feedback-driven lifelong learning. By incorporating …

Learnable Structured Attention For Student-Aware Knowledge Distillation In Dense Prediction, Chen Liu

ETDs from 2020-2029

Dense prediction tasks, including object detection and semantic segmentation, require models to produce structured predictions and are widely used in real-world vision applications. Although deep networks have achieved strong performance on these tasks, their high computational cost limits deployment on resource-constrained systems such as autonomous-driving vehicles. Knowledge distillation (KD) addresses this issue by transferring knowledge from a large teacher model to a compact student model. However, existing distillation methods for dense prediction face greater challenges than those for classification due to the more complex task requirements. To overcome the challenges, this thesis presents a unified study of adaptive distillation for …

From Cork To Coasting: A Multi-Stage Ode Model Of Water-Rocket Flight, Viktoria Savatorova, Patryk Kustra, Ethan Dyer, Connor Carlson, Aleksei Talonov

CODEE Journal

Water rockets provide an affordable and engaging context for exploring applications of differential equations. Motivated by outreach activities conducted with undergraduate students, we develop a four-stage mathematical model of vertical water-rocket flight that is suitable for use in an ODE or mathematical modeling course. The model includes the cork-release phase, water-thrust propulsion, air-thrust propulsion with compressible and potentially choked flow, and the final ballistic stage with quadratic drag. While retaining key physical features, the model can be formulated as a system of ordinary differential equations that can be integrated numerically using tools familiar to students. We compare model predictions with …

A Modular Saponin Adjuvant Platform: Development, Structure–Activity Relationships, And Applications, Di Bai

ETDs from 2020-2029

ABSTRACT Saponin-based vaccine adjuvants have attracted considerable attention owing to the clinical success of QS-21, a potent immunostimulant capable of inducing balanced humoral and cellular immune responses, yet its widespread application is limited by supply constraints, chemical instability, and dose-dependent toxicity. To address these challenges, we previously developed two semisynthetic saponin adjuvants, VSA-1 and VSA-2, derived from abundant Momordica saponins through a single-step modification, which exhibit QS-21–comparable immunopotentiating activity with improved accessibility and stability. Here, we first performed a systematic structure–activity relationship (SAR) study of the VSA series using MS I as the lead scaffold. Modulation of the side-chain length …

Active Learning Of Constraint Boundaries Using Expected Magnitude Of Incorrectness And Neural Networks, Atticus Beachy, Ramana V. Grandhi

Faculty Publications

This research proposes an acquisition function for constraint boundary identification, with applications to hypersonic air vehicles. Hypersonic vehicles endure extreme thermal loads caused by aerodynamic heating, resulting in a strong coupling between structural performance and aerothermodynamics. However, modeling coupled system behaviors requires simultaneous consideration of both aerodynamic and structural design variables, increasing the dimensionality of the design trade space and the difficulty of accurately modeling the constraints. Several active learning schemes have been proposed to accelerate identification of the composite feasible region that satisfies all constraints. Some of these require integrating the surrogate model over the entire design space with …

Physically Mixed Graphene Aerogel:Carbon Black (Ga:Cb)-Supported Pt Or Hydrothermally Synthesized Ga-Pt/Cb Hybrid Electrocatalysts For Pem Fuel Cells, Emi̇ne Teke Öner, Meli̇s Irmak Aydin, Merve Ni̇da Dursunoğlu, Ayşe Bayrakçeken

Turkish Journal of Chemistry

Graphene aerogels (GAs), having the superior properties of graphene and aerogel structures, are promising support materials for Pt nanoparticles to be used as electrocatalysts for PEM fuel cells. In this study, two routes were followed to synthesize GA-based electrocatalysts. In the first route, after GA synthesis it was physically mixed with carbon black (CB) by changing the mass ratios from 0% to 100% with 25% increments and then decorated with Pt nanoparticles via microwave irradiation, resulting in Pt/GA:CB electrocatalysts. In the second route, firstly, Pt/CB electrocatalyst was synthesized and then GA was hydrothermally added to the Pt/CB by changing the …

Amending Planting Media With Typha-Derived Biochar For Sustainable Horticulture, Elissa Touma

USF Tampa Graduate Theses and Dissertations

Constructed wetlands are widely used to improve water quality by removing excess nutrients from wastewater and stormwater. Nutrients are stored within wetland vegetation, particularly in fast-growing plants such as Typha. Harvesting vegetation provides an opportunity to permanently remove these nutrients while generating biomass suitable for beneficial reuse. Converting harvested biomass into value-added products such as compost and biochar can support nutrient recovery and sustainable biomass management. In addition, increasing concerns regarding the environmental impacts of peat extraction have created interest in renewable alternatives for horticultural growing media. Therefore, the objective of this study was to evaluate the potential of harvested …

Modeling And Mitigating Stale Hardcoded Secrets In Version Control History, Katarina Valentine Capalbo

USF Tampa Graduate Theses and Dissertations

Hardcoded secret vulnerabilities remain a growing and persistent problem that can be difficult to mitigate once exposed. While there has been significant research and advancements in identifying and preventing hardcoded secrets, less attention has been given to understanding the risks of leaving these secrets behind in version control history, as well as analyzing the sanitization of hardcoded secrets. These challenges present a growing gap between the risk and ability to mitigate and sanitize existing secret exposures. This thesis begins to address this gap by formalizing a threat model for hardcoded secrets that persist in Git version control history after the …

Development Of An Adaptive Pelican Crossing Model Using Fuzzy Logic In Mixed Traffic Conditions, Manazil Adam, Andyka Kusuma, R. Jachrizal Sumabrata

Smart City

Traffic management at at-grade pedestrian crossing facilities (pelican crossings) in highly populated areas, such as the Universitas Indonesia Station, faces significant inefficiency challenges. During peak hours, the fixed-time system is frequently disabled and replaced with subjective manual control by security personnel, thereby triggering irregular stop-and-go cycles and a high accumulation of vehicle delays. This study aims to develop a hybrid adaptive control model integrating Computer Vision, Genetic Algorithm (GA), and Fuzzy Logic to optimize intersection performance under mixed traffic conditions. The research methodology begins with the extraction of traffic and pedestrian characteristic data, calculated manually through recorded field observations. This …

Spatial Tax Intelligence: Implementing Integrated Spatial Decision Support Systems For Smart Urban Governance, Wildan R. Irfana, Haldis A. Bahar, Muhammad H. Candra

Smart City

The transition toward smart governance requires local governments to adopt data-driven policy approaches, particularly in managing urban tax capacity. However, tax administration in many developing regions remains predominantly tabular and administrative, limiting the ability to capture the spatial dynamics of economic activities. This reveals a critical knowledge gap, as integrated frameworks combining spatial and tax data to identify geographic disparities in tax performance remain limited. Consequently, areas with high economic activity but low tax compliance, referred to as tax blind spots, often remain undetected. This study aims to analyze the effectiveness of integrating spatial and tax data in identifying spatial-tax …

The Effect Of Project-Based Learning Model On Entrepreneurship (Pjbl-E) With A Deep Learning Approach On Students' Problem-Solving And Cognitive Skills, Ricce Oktasari, Irwandi Irwandi, Siti Darwa Suryani

Jurnal Pendidikan Sains

This study aims to examine the effect of the Entrepreneurship-based Project Based Learning (PjBL-E) model integrated with a pedagogical Deep Learning approach on students’ problem-solving skills and cognitive learning outcomes in biology learning. The novelty of this study lies in the integration of entrepreneurship values and pedagogical deep learning principles into Project Based Learning to create contextual and meaningful learning experiences. Entrepreneurship integration encourages students to develop innovative products, identify real-world problems, and apply biological concepts in practical and socio-economic contexts. Meanwhile, the pedagogical Deep Learning approach promotes reflective thinking, conceptual understanding, critical analysis, and the ability to connect theory …

High-Throughput Optical Analysis To Inform Design Of Electrochemical Biosensors, Nathan J. Ricks, Michael A. Pence, Monica Brachi, Shelley D. Minteer

Chemistry Faculty Research & Creative Works

Electrochemical biosensors are central to wearable diagnostics, point-of-care testing, and continuous health monitoring due to their low power requirements, compatibility with miniaturized electronics, and proven clinical impact. Despite these advantages, the development of new electrochemical biosensors remains slow, constrained by limited throughput, complex electrode–biomolecule interfaces, and challenges associated with selectivity and performance in chemically complex environments. This perspective outlines how the next generation of electrochemical biosensors can be enabled by decoupling high-throughput front-end discovery and optimization from electrochemical readouts using nonelectrochemical surrogate assays. Optical, affinity, and cell-sorting platforms, including SELEX, fluorescence-activated cell sorting, and chemically coupled fluorescence assays, allow orders-of-magnitude …

Learning In Infants Using Intrinsically Motivated Goal Conditioned Reinforcement Learning, T I Darsan

Master’s Dissertations

Traditional artificial intelligence models learn by passively digesting large datasets. In contrast, human infants discover skills by actively interacting with their bodies and environments without explicit external rewards. This thesis introduces the Composer Architecture, a machine learning framework designed to mimic this autonomous, open-ended development. The Composer architecture operates in a multi-stage loop, the latent model using Contrastive Learning Through Time (CLTT) to compress high-dimensional raw data from visual, proprioceptive, and touch sensors into a low-dimensional space. To preserve data relationships and prevent topological collapse, a Softmax activation forces these latent representations to lie smoothly on a probability simplex. A …