Digital Commons Network^™

(R2175) Application Of Similarity Measures On Bipolar Complex Neutrosophic Matrices In United Nations’ Sdg-17 Using Python, T. Muthuraji, N. Krishnapraveen

Applications and Applied Mathematics: An International Journal (AAM)

The increasing complexity of decision-making environments demands mathematical frameworks capable of modeling bipolar, indeterminate, and phase-dependent uncertainty simultaneously. Bipolar Complex Neutrosophic theory provides such a structure, but the extension of similarity measures to matrix-based environments remains largely unexplored. In this study, we formally develop cosine, Dice, Jaccard, and hybrid vector similarity measures for Bipolar Complex Neutrosophic Matrices (BCNMs). Each matrix element is represented by a Bipolar Complex Neutrosophic Number (BCNN), enabling structured representation of multidimensional uncertainty within a matrix framework. We also design and implement efficient Python-based computational tools to automate similarity evaluation for BCNMs. The proposed algorithms reduce computational …

(R2191) The Study Of Stokes Drag In The R4bp Under The Effect Of Coriolis And Centrifugal Forces With Variable Mass, Amit Mittal, Krishan Pal, Rajiv Aggarwal, Rajveer Singh

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we examine the existence, locations, and stability of the equilibrium points under the combined effects of Stokes drag and small perturbations in the Coriolis and centrifugal forces in the triangular restricted four-body problem (TR4BP) with variable mass. A triangular (Lagrangian) configuration is formed by the three primary bodies, which occupy the vertices of an equilateral triangle. All the primaries are treated as point masses to study the dynamical behavior of an infinitesimal body. The numerical results indicate that, under the influence of Stokes drag, none of the equilibrium points lie along a straight line. The centrifugal force …

(R2140) Verifying The Proper Efficiency In Multi-Objective Problems, Javad Bavali, Hadi Basirzadeh

Applications and Applied Mathematics: An International Journal (AAM)

Over the past decade, numerous approaches have been put forward to address multi-objective optimization problems-focusing on approximating proper efficient solutions instead of the efficient solutions. These methods are important because, according to Geoffrion’s conjecture, proper non-dominated solutions constitute a dense subset of the non-dominated solution set. In the current study, first, using the definition of Kuhn-Tucker’s proper efficiency, we present a linear subproblem that investigates the proper efficiency of a randomly selected feasible point. Additionally, the relationship between the different types of solutions to this sub-problem and the proper efficient solutions of the main problem has been analyzed. Next, we …

Atropisomer Mechanochemistry Of Diarylethene Mechanophores: A Study Of Structure-Mechanical Activity Relationships, Cijun Zhang

Dissertations - ALL

Stimuli-responsive organic structures are advanced, intelligent platforms that dynamically adjust their physical or chemical properties—such solubility, or color—in response to external stimuli including light, heat, pH, redox conditions, mechanical force, or magnetic fields. Among these structures, mechanophores represent an important class that is specifically responsive to mechanical force. Synthetic mechanophores can be rationally engineered to exhibit tunable mechanosensitivity as well as tailored chemical and physical properties. In this work, we designed and synthesized a type of atropisomeric mechanophores based on sterically congested diarylethene photoswitches, and systematically investigated their mechanical and photochemical properties. Chapter 1 Chapter 1 provides a general introduction …

From Detection To Segmentation: A Foundation Model Approach To Organoid Brightfield Image Analysis Using Sam 3, Hiren Manani

Theses - ALL

This thesis presents the first systematic application of SAM 3, a unified foundation model for promptable segmentation, to mouse small intestinal organoid brightfield microscopy image analysis. The work spans the complete pipeline from zero-shot baseline evaluation through domain-specific fine-tuning on a GPU cluster, and documents the full engineering process required to adapt a state-of-the-art foundation model to a novel biomedical imaging domain. A comprehensive literature review of over 20 papers spanning detection-based, classical segmentation, foundation model, and morphological analysis approaches identified a clear research gap that this thesis addresses. Five critical compatibility patches were developed to deploy SAM 3 on …

Multi-Modal Survival Prediction On Breast Cancer Mammograms And Enabling Multi-Institutional Collaborations With Federated Learning, Nikolas Koutsoubis

USF Tampa Graduate Theses and Dissertations

Cancer remains one of the leading causes of mortality worldwide, and machine learning is well positioned to leverage the large volumes of routinely collected clinical and imaging data to improve patient outcomes. Realizing this potential at scale requires three capabilities that current practice does not yet deliver in combination: models that integrate the multiple data modalities clinicians use, training procedures that respect institutional data-sharing constraints, and tooling that enables sharing of de-identified data when federated approaches are not sufficient. This dissertation develops methods and infrastructure addressing each of these capabilities in the context of breast cancer and oncology more broadly. …

Instructions To Authors, Academy Editors

Journal of the Arkansas Academy of Science

No abstract provided.

Building Trustworthy Information Systems: A Unified Framework For Comparative Risk Detection, Parisa Momeni

USF Tampa Graduate Theses and Dissertations

Risk detection in large scale information systems increasingly depends on heterogeneous data generatedby both centralized and distributed ecosystems. While centralized systems provide curated and validated reports, distributed environments produce large-scale and real-time observational evidence. Existing computational approaches analyze these ecosystems in isolation, limiting systematic comparison of risk repre-sentations across heterogeneous sources.

This dissertation presents a unified computational framework for comparative risk detection across centralized and distributed information systems. The framework provides a domain independent methodology for transforming heterogeneous risk reporting data into comparable multidimensional representations. To enable interpretable comparison of heterogeneous risk distributions, this work introduces the Geometric Overlap Score …

Qualitative Analysis Of Solutions To A General Class Of Nonlinear Difference Equations With Applications, Osama Moaaz, Mohamed F. Abouelenein, Mona Anis

Mathematical Modelling and Numerical Simulation with Applications

This work examines the qualitative behavior of a general class of difference equations. We establish criteria guaranteeing the stability, periodicity, and boundedness of the solutions of the equation under consideration. In addition, we identify its invariant intervals. The theoretical results are subsequently applied to various special cases, among them the May--Host model. Numerical simulations are presented to demonstrate the dynamics of the solutions and to validate the theoretical analysis.

Portable Trace Gas Analysis With Multipass Cavity Raman Scattering, Charuka Muktha Arachchige

USF Tampa Graduate Theses and Dissertations

The continual increase in the production and utilization of chemicals across a growing range of industrial, environmental, and medical applications necessitates accurate and efficient measurement of molecular composition. Trace gas detection is particularly critical in industrialized settings, where the identification of colorless and odorless gases is essential for ensuring operational safety and regulatory compliance. Recent advances in optical instrumentation have positioned spontaneous Raman scattering as a promising analytical technique for trace gas analysis, with multipass cavity enhancement providing a cost-effective pathway to high detection sensitivity. However, existing implementations remain confined to laboratory-scale optical table setups, limiting their applicability in field …

Designing For Fitness And Resilience In Human Artificial Intelligence Systems, Thomas R. Gill

USF Tampa Graduate Theses and Dissertations

Over the last decade, new artificial intelligence models, frameworks, and applications have emerged that have radically changed the socio-technical landscape. These new technologies represent both great opportunities and great potential risks. Due to the recency of their emergence, there is little known about the longevity and long-term repercussions of artifacts powered by new artificial intelligence technology. In this dissertation, I evaluate A.I. and A.I.-based artifacts through the lens of the fitness-utility model, a tool developed by Gill and Hevner (2013) for the evaluation of an artifact's ability to survive and reproduce over long time horizons. In so doing, I also …

The Soil Crisis In Modern Food Systems: Rethinking Agricultural Land Use, Antonia Moure Richard

Journal of Food Law & Policy

Feeding a larger world while preserving the resource that makes agriculture possible—soil—poses a governance problem. By 2050, food systems must support 9.8 billion people even as prevailing practices continue to degrade soils that are non-renewable on human timescales. Technological fixes (e.g., vertical farming, hydroponics) may complement production, but they cannot substitute for soil at scale. The question that follows is simple: are current uses of soil compatible with the future needs of food systems? This article argues that without a shift in governance, short-run productivity gains are achieved by drawing down the soil asset, thereby undermining long-run food security and …

Supersymmetric Quantum Fields Via Quantum Probability, Radhakrishnan Balu

Journal of Stochastic Analysis

The super version of imprimitivity theorem is available now to describe global supersymmetry of systems using the representations of super Lie groups (SLG). This result uses the equivalence between super Harish- Chandra pairs and super Lie groups, at the categorical level, and is applicable to super Poincaré group and generalizes a smooth SI to super context. We apply the result to build supersymmetric quantum fields. Towards this end, we set up a super Fock space of a disjoint union of super Hilbert spaces which is equivalent to super tensoring of boson (even) part symmetrically and that of fermion (odd) part …

Photoluminescent Studies Of Metal-Organic Frameworks For Small Molecule Sensing, Julia T. Dematteo

USF Tampa Graduate Theses and Dissertations

Metal–organic frameworks (MOFs) are highly tunable nanoporous materials with broad applications in gas separation, drug delivery, light harvesting, and chemical sensing. The incorporation of photoactive components into MOFs enables the development of optical sensors capable of detecting a wide range of analytes. Porphyrins and metalloporphyrins are particularly attractive for such applications due to their high molar absorptivity, strong emission quantum yields, and versatile interactions with chemical species.

In this work, two porphyrinic MOFs, PCN-222 and MOF1(Cd), are investigated. Both frameworks utilize tetrakis(4-carboxyphenyl)porphyrin (TCPP) as the organic linker, imparting optical functionality to the materials. Integration of TCPP into the framework induces …

To What Extent Could Quantum Computing Pose A Threat To Global Modern Data Security?, Aniket Maheshwari

Journal of Cybersecurity Education, Research and Practice

Quantum computing has emerged as a transformative technology with the potential to fundamentally disrupt modern cryptographic systems that underpin global data security. This paper examines the extent to which quantum computing could pose a threat to modern global data security by synthesising existing technical, institutional, and policy-oriented literature. Drawing on a narrative review of scholarly research, industry reports, and government frameworks, the analysis focuses on the implications of quantum algorithms such as Shor’s and Grover’s, which challenge the mathematical foundations of widely used cryptographic schemes. The findings suggest that while quantum computing presents a credible long-term threat to asymmetric encryption …

Editorial: Plant Responses To Abiotic Stress: Unraveling Complex Mechanisms Through Genomics And Physiology, Mizanur Rahman, Takashi Asaeda, Md Harun Rashid

School of Earth, Environmental, & Marine Sciences Faculty Publications

No abstract provided.

Van Der Waals Interactions Through The Lens Of 2d Materials With Emphasis On Many-Body Effects, Thi Xuan Diem Dang

USF Tampa Graduate Theses and Dissertations

This dissertation addresses the long-standing challenge of accurately and efficiently modeling long-range electron correlations, with a particular focus on van der Waals (vdW) interactions. These interactions play an essential role in predicting the structure, stability, and functionality of molecular systems and condensed matter materials. Although Density Functional Theory (DFT) has become a robust cornerstone of computational materials science, traditional formulations of the theory frequently fail to capture dispersive interactions, leading to significant errors in determining interlayer distances, binding energies, and stacking configurations. These limitations become particularly pronounced in layered materials and vdW heterostructures (HSTs), where weak long-range correlations are sensitive …

Gw230814: Investigation Of A Loud Gravitational-Wave Signal Observed With A Single Detector, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Miriam Ramos Arevalo, Wenhui Wang

Physics & Astronomy Faculty Publications

GW230814, detected by the LIGO Livingston observatory with a signal-to-noise ratio of 42.4, represents the loudest gravitational-wave signal in the GWTC-4.0 catalog. Its source is consistent with a binary black hole coalescence with component masses m1=33.7+2.9−2.2M⊙, m2=29.9+2.1−2.8M⊙, and a small effective inspiral spin χeff=−0.01+0.06−0.07. The high signal-to-noise ratio enabled us to detect an ℓ = ∣m∣ = 4 mode in the inspiral–merger–ringdown signal for the first time (with Bayes factor ≈10), as well as enabling a range of tests of consistency between theoretical predictions and the observed waveform. While most of these tests show agreement with theoretical predictions, there are …

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 …

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 …

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, …

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 …

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 …

Kernelizing Protein Interaction Languages: Spectral Approximations And Random Fourier Features, Aishik Ghosh

Master’s Dissertations

Protein-peptide interactions play an important role in many biological phenomena, spanning adaptive immunity to disease pathology. In the Sliding Window Interaction Grammar (SWING) framework, interactions are represented as sequences of biochemical tokens embedded using Doc2Vec, allowing robust generalisation to unobserved MHC alleles. However, classification remains limited to a single Euclidean feature space that is incapable of resolving binding landscapes. This dissertation develops SWING for four distinct kernel types: Gaussian, Laplacian, anisotropic (ARD), and the Spectral Mixture (SM) kernel, each approximated using scalable Random Fourier Features. The SM kernel incorporates prior knowledge about secondary structure into its spectral density as biological …

State Government, The Forgotten Cyber Actor, Joshua D. Strubel

Doctoral Dissertations and Projects

Cyber incidents are among the most pervasive threats facing the United States, with the FBI recording over 859,000 reported attacks and an estimated $16.6 billion in losses in 2024 alone. Despite widespread recognition that effective cyber defense requires a whole-nation approach, the existing research literature overwhelmingly focuses on federal policy, leaving state governments as largely overlooked actors. This study addresses that gap by examining the research question: How does state cybersecurity policy affect malicious cyber actors' frequency of operations? Drawing on multilinear regression analysis augmented by Random Forest machine learning models, this study evaluates the relationship between state-level cyber deterrence …

Student Worksheets Based On The Local Wisdom Of Besilek Serawai For Sixth-Grade Elementary Science Learning, Mice Agustin, Tomi Hidayat, Irwandi Irwandi

Jurnal Pendidikan Sains

This study aims to develop a Student Worksheet (Lembar Kerja Peserta Didik [LKPD]) based on the local wisdom of Besilek Serawai for sixth-grade elementary science education and to evaluate its validity. The study employed the ADDIE development model, consisting of five stages: Analyze, Design, Develop, Implement, and Evaluate. The developed LKPD integrates Besilek Serawai, a traditional martial art of the Seluma community, with the concept of the human locomotor system in science instruction. The worksheet was validated by two subject-matter experts and two media experts. Material validation yielded an average score of 4.26, equivalent to a validity percentage of 85.2%, …

Design And Evaluation Of A Code-Switching-Aware Multilingual Conversational Ai System Using Advanced Rag Architectures, Ashutosh Juvale

Master’s Dissertations

Conversational artificial intelligence has become the primary interface through which hundreds of millions of users in India seek information and customer support. Yet the way these users actually write and speak is fundamentally at odds with the monolingual assumptions baked into most retrieval and generation systems: they code-switch, fluidly mixing one or more of the twenty-two scheduled languages of India with English, frequently typing Indic words in the Roman script ("mera refund kab tak aayega"). Standard Retrieval-Augmented Generation (RAG) pipelines silently fail on such input — the retriever returns off-topic passages because the query and the knowledge base live in …

Morphodynamic Evolution Of Midnight Pass, West-Central Florida, Sydney C. Scott

USF Tampa Graduate Theses and Dissertations

This study takes advantage of a rare opportunity provided by the reopening of Midnight Pass due to two consecutive hurricanes in 2024, to examine the morphologic evolution of a newly reopened inlet and subsequent beach-inlet interactions. Historical aerial photos since the 1940s were collected and analyzed to understand the last closure of Midnight Pass, and to gain knowledge on the future of the newly reopened inlet. Time-series topography and bathymetry survey of the beach-inlet system were conducted bimonthly to quarterly for the first year and a half after the reopening, with the goals of quantifying the morphologic changes and understanding …

Learning To See Lesions, Not Skin Tone: Counterfactual Multimodal Learning For Fair, Trustworthy, And Text-Free Dermatology Ai, Shivam Jangid

Master’s Dissertations

Recent advances in deep learning have significantly improved the performance of automated skin lesion classification systems, enabling accurate detection of various dermatological conditions from medical images. Despite these achievements, concerns regarding fairness and generalization remain a major challenge for the deployment of such systems in real-world clinical settings. A key factor contributing to these challenges is the presence of bias in training datasets, particularly with respect to skin-tone representation. Most publicly available skin lesion datasets contain a disproportionate number of samples from individuals with lighter skin tones. As a result, deep learning models trained on these datasets often learn representations …