Digital Commons Network^™

Efficient Photocatalytic Core–Shell Synthesis Of Titanate Nanowire/Rgo, Xiaofang Ye, Yang Tian, Mengyao Gao, Fangjun Cheng, Jinshen Lan, Han Chen, Mark Lanoue, Shengli Huang, Z. Ryan Tian

Chemistry & Biochemistry Faculty Publications and Presentations

Wide bandgap semiconductor-based photocatalysts are usually limited by their low solar energy conversion efficiency due to their limited absorption solar wavelength, their rapid surface recombination of the photogenerated electron–hole pairs, and their low charge-carrier mobility. Here, we report a novel stepwise solution synthesis for achieving a new photocatalytic core–shell consisting of a titanate nanowire/reduced graphene oxide shell (or titanate/rGO) 1D-nanocomposite. The new core–shell nanocomposite maximized the specific surface area, largely reduced the charge transfer resistance and reaction energy barrier, and significantly improved the absorption of visible light. The core–shell nanocomposites’ large on/off current ratio and rapid photo-responses boosted the photocurrent …

Tort Theory And The Restatement, In Retrospect, Keith N. Hylton

Faculty Scholarship

This is my third paper on the Restatement (Third) of Torts. In my first paper, The Theory of Tort Doctrine and the Restatement (Third) of Torts, I offered a positive economic theory of the tort doctrine that had been presented in the Restatement (Third) of Torts: General Principles, and also an optimistic vision of how positive theoretical analysis could be integrated with the Restatement project. In my second paper, The Economics of the Restatement and of the Common Law, I set out the utilitarian-economic theory of how the common law litigation process could generate optimal (efficient, wealth-maximizing) rules and compared …

A Study Of The Effect Of Preparation Parameters On The Mechanical Properties Of Freeze-Dried Gelatin-Elastin-Hyaluronate Scaffolds, Mansour Qamash

Master's Theses (2009 -)

This thesis is dedicated to a detailed study of changes in the properties of Gelatin-Elastin-Hyaluronate (GEH) tissue engineering scaffold resulting from changes in preparation parameters. More specifically, utilizing a combination of foaming and freeze-drying techniques, this research investigates the effects of different parameters, including agitation speed, duration time, and chilling temperature on the scaffold’s structural integrity, porosity, and mechanical properties. The methodology involves a carefully calibrated process in which the scaffold matrix is initially prepared by incorporating 8% gelatin, 2% elastin, and 0.5% hyaluronate (w/v) into a homogenous aqueous solution, followed by controlled agitation and subsequent freezing at designated temperatures. …

Efforts Toward Difunctionalization Of (Hetero)Arenes Enabled By Visible Light, Eric Allen

Master's Theses (2009 -)

Functionalized arenes and heteroarenes are ubiquitous motifs in natural products, pharmaceuticals, and functional materials. As such, methods to place multiple functionalities on (hetero)arenes in one synthetic step create molecular complexity quickly and are highly valued. The vast majority of current strategies are metal-mediated, although others such as utilizing aryne intermediates and cycloadditions have also been reported. The premier challenge in this research area is the difficulty in controlling regioselectivity. Strategies of controlling regioselectivity have included tuning the electronic nature of the substrate, the use of directing groups (DGs), steric influences, ligand control, and photochemically initiated methods. Certain strategies tend to …

The Evolution Of Agrarian Landscapes In The Tropical Andes, Courtney Shadik, Mark B. Bush, Bryan G. Valencia, Angela Rozas-Davila, Daniel Plekhov, Robert D. Breininger, Multiple Additional Authors

Anthropology Faculty Publications and Presentations

Changes in land-use practices have been a central element of human adaptation to Holocene climate change. Many practices that result in the short-term stabilization of socio-natural systems, however, have longer-term, unanticipated consequences that present cascading challenges for human subsistence strategies and opportunities for subsequent adaptations. Investigating complex sequences of interaction between climate change and human land-use in the past—rather than short-term causes and effects—is therefore essential for understanding processes of adaptation and change, but this approach has been stymied by a lack of suitably-scaled paleoecological data. Through a highresolution paleoecological analysis, we provide a 7000-year history of changing climate and …

“Art For The Millions:” The Evolution Of Informal Learning From The Charleston Museum To The New Deal, Kristen Walker

Theses

The advent of the first museum in the United States in 1773, The Charleston Museum, sparked a shift in the way education is perceived and how it can be conducted. However, only recently has the intentional implementation of programs and exhibitions been created in a digestible way for the public. This thesis discusses how informal learning has evolved since the establishment of the Charleston Museum and the legacy of the Federal Art Project regarding informal learning and art education. Key research methods include the examination of primary and secondary resources, including oral histories held by the Smithsonian Archives of American …

Exploring Situational Factors For Female International Students And Their Satisfaction In Higher Education Using Cb-Sem, Dian Fu Chang, Angel Chang, Cheng Yi Kang

Faculty Research, Scholarly, and Creative Activity

While the topic of attracting and maintaining inbound international students has received much scholarly attention in higher education, attracting female international students has rarely been discussed. This study addresses the issue of attracting degree-seeking female international students. Based on the notion of situational factors and total quality management (TQM), we assumed both institutional design and students’ satisfaction are core concepts for attracting and retaining female international students that will make a difference in higher education. A total of 215 survey responses were analyzed, and a covariance-based structural equation modeling (CB-SEM) approach was developed. The results confirm female international students’ perception …

On Local Antimagic Chromatic Number Of Graphs With Cut-Vertices, Gee Choon Lau, Wai Chee Shiu, Ho Kuen Ng

Faculty Research, Scholarly, and Creative Activity

An edge labeling of a connected graph G = (V, E) is said to be local antimagic if it is a bijection f: E → {1, …, |E|} such that for any pair of adjacent vertices x and y, f+ (x) ≠ f+ (y), where the induced vertex label f+ (x) =∑ f(e), with e ranging over all the edges incident to x. The local antimagic chromatic number of G, denoted by χla (G), is the minimum number of distinct induced vertex labels over all local antimagic labelings of G. In this paper, the sharp lower bound of the local …

Optimization Of Sensor Placement For Modal Testing Using Machine Learning, Todd Kelmar, Maria Chierichetti, Fatemeh Davoudi Kakhki

Faculty Research, Scholarly, and Creative Activity

Featured Application: This study introduces an innovative approach for optimizing sensor placement in modal testing by applying machine learning with enhanced efficiency and precision. Modal testing is a common step in aerostructure design, serving to validate the predicted natural frequencies and mode shapes obtained through computational methods. The strategic placement of sensors during testing is crucial for accurately measuring the intended natural frequencies. However, conventional methodologies for sensor placement are often time-consuming and involve iterative processes. This study explores the potential of machine learning techniques to enhance sensor selection methodologies. Three machine learning-based approaches are introduced and assessed, and their …

Optimizing Supply Chain Dynamics Using Machine Learning, Mohammad Zubin Siddiqui

Theses

Supply chains face many challenges in today’s business environment. This paper examines how advanced analytics can be used to improve supply chain efficiency and resilience with a particular focus on demand forecasting and late delivery analysis. The thesis focuses on two areas, which are forecasting demand and analyzing late deliveries. With the help of data-driven models for forecasting demand and pinpointing reasons behind delayed shipments, establishments can take appropriate measures that will reduce risks and enhance operational efficiency. A complete analytic framework is suggested that integrates sophisticated analytics into supply chain management so that organizations can optimize all their operations …

Robust Machine Learning Under Vulnerable Cyberinfrastructure And Varying Data Quality, Sergei Chuprov

Theses

In our study, we investigate Machine Learning (ML) application robustness in ML Integrated with Network (MLIN) systems. We consider MLIN as an integration of three major components and interrelations between them: data sources, network facilities, and ML application. In contrast to the conventional approaches that focus on each separate component, we concentrate on their interrelationships, and consider them from the system integration perspective. We formulate our primary goal as to develop methods and tools aimed at assuring ML application performance towards Data Quality (DQ) variation in MLIN through improving ML application robustness. We examine the prior work on ML robustness …

Predictive Analytics Of Road Traffic Incidents, A Machine Learning Approach, Maryam Essa Jaji

Theses

Traffic accidents rank among the world's most serious concerns due to the high number of deaths, injuries, and fatalities as well as the enormous financial losses they cause every year. Road travel is a necessary component of modern civilization, but because of the rise in traffic accidents, it costs the world economy billions of dollars and over a million deaths annually. Road accidents can be caused by a variety of elements. It can be possible to take action to lessen the severity and extent of the effects if these elements are better recognized and predicted. The goal of this project …

Comparison Of Emissions Across Tobacco Products: A Slippery Slope In Tobacco Control, Ahmad El-Hellani, Ayomipo Adeniji, Hanno C. Erythropel, Thomas Lamb, Qixin Wang, Vladimir Mikheev, Robert Strongin, Multiple Additional Authors

Chemistry Faculty Publications and Presentations

In this narrative review, we highlight the challenges of comparing emissions from different tobacco products under controlled laboratory settings (using smoking/ vaping machines). We focus on tobacco products that generate inhalable smoke or aerosol, such as cigarettes, cigars, hookah, electronic cigarettes, and heated tobacco products. We discuss challenges associated with sample generation including variability of smoking/vaping machines, lack of standardized adaptors that connect smoking/vaping machines to different tobacco products, puffing protocols that are not representative of actual use, and sample generation session length (minutes or number of puffs) that depends on product characteristics. We also discuss the challenges of physically …

Accommodating Spatio-Temporal Dependency In Airline Demand Modeling, Sudipta Dey Tirtha, Tanmoy Bhowmik, Naveen Eluru

Civil and Environmental Engineering Faculty Publications and Presentations

The objective of the current study is to examine monthly air passenger departures at the airport level considering spatial interactions between airports. In this study, we develop a novel spatial grouped generalized ordered probit (SGGOP) model system of monthly air passenger departures at the airport level. Specifically, we estimate two variants of spatial models including spatial lag model and spatial error model. In the presence of repeated demand measures for the airports, we also consider temporal variations of spatial correlation effects among proximally located airports by employing space and time-based weight matrix. The proposed model is estimated using monthly air …

A Laplace-Based Model With Flexible Tail Behavior, Cristina Tortora, Brian C. Franczak, Luca Bagnato, Antonio Punzo

Faculty Research, Scholarly, and Creative Activity

The proposed multiple scaled contaminated asymmetric Laplace (MSCAL) distribution is an extension of the multivariate asymmetric Laplace distribution to allow for a different excess kurtosis on each dimension and for more flexible shapes of the hyper-contours. These peculiarities are obtained by working on the principal component (PC) space. The structure of the MSCAL distribution has the further advantage of allowing for automatic PC-wise outlier detection – i.e., detection of outliers separately on each PC – when convenient constraints on the parameters are imposed. The MSCAL is fitted using a Monte Carlo expectation-maximization (MCEM) algorithm that uses a Monte Carlo method …

Low Power Logic Locking Using Design Space Modeling To Achieve System-Wide Security, Long Lam

Theses

Rising design complexity and smaller technology nodes are escalating fabrication costs, prompting design houses to outsource to untrusted external facilities, which raises trust and privacy concerns. These concerns stem from the risk of security breaches like IP piracy, reverse engineering, and hardware trojans. The critical need to protect design intellectual property prompted the development of logic locking, a combinational hardware security technique that corrupts the functionality of a design without the correct secret key. However, the effectiveness of logic locking varies substantially based on how and where it is implemented within a system, including the specific technique families selected, the …

Novel Methods For Modeling And Treating Biofilm Infections, Emily Lazarus

Theses

Biofilms are responsible for the development of chronic infections, which are 10-1000 times more resistant to antimicrobial agents than two-dimensional (2D) planktonic culture. Traditionally, 2D planktonic cultures are used to study efficacy of antimicrobial treatments but 2D cultures have several shortcomings such as increased sensitivity to treatments, lack of complexity of the three-dimensional (3D) environment, limited host defense mechanisms, and lack the structural thickness of natural biofilms. Biofilm-related infections play a critical role in the delayed healing process of chronic skin wounds, and while treatments for chronic skin wounds exist, including negative pressure wound healing (NPWT), biofilm infections still prevail. …

Improving Adaptation Of Deep Learning With Inductive Bias, Xiajun Jiang

Theses

Human intelligence is strong at adapting to a small number of observations, partially because of the human ability to 1) use given knowledge and 2) distill knowledge from related but different data to guide learning for future tasks, where such ability is the inductive bias during learning. Deep learning shows a promising solution to artificial intelligence. However, generalizing or adapting deep learning models to heterogeneous tasks remains an open question. Existing data-driven models often ignore prior knowledge about the underlying problems of interest, or have limitations in incorporating complex knowledge into neural networks. The one-size-fit-all formula assumes the training and …

Hierarchical Parameterization In Spherical Domains For Deforming Feature Alignment, Lizhou Cao

Theses

The growing interest in immersive technology and lifelike virtual worlds has underscored the importance of creating automated methods to generate characters with a wide range of morphological variations. Traditional methods have either depended heavily on manual effort or simplified the challenge by only addressing static meshes or basic deformation transfers, without supporting dynamic shape morphing with deformation. In this work, we introduce a novel method that leverages cross-parameterization to semi-automate the creation of characters that are not only morphologically varied but also capable of synthesized deformation and animations. The key innovation of our work lies in the parameterization of deforming …

Predictive Maintenance On Drone Batteries Failure Using Machine Learning, Khalifa Jamal Almannaei

Theses

Predictive maintenance, powered by machine learning models, presents an innovative solution to address the limitations of drone battery maintenance. The core aim of this study is to design and implement machine learning models suitable for drone batteries, predict battery health, and prescribe maintenance actions. The ultimate scope is to improve operational reliability, safety, and cost-efficiency for drone applications while advancing sustainability and efficiency within the drone industry. By integrating predictive maintenance, the management of drone batteries can be optimized, leading to more reliable, and cost-effective drone operations, the proposal will seek to identify different factors that impacts the health and …

Optimizing V2v Energy Exchange Using Ai, Marwa Alghawi

Theses

A key factor in promoting sustainable economies, industries, and society is the use of electric vehicles (EVs). They are an important step toward a greener future since they reduce greenhouse gas emissions, improve air quality, and encourage energy independence. The demand for charging stations (CSs) will undoubtedly rise as the global EV market continues to grow over the next few decades, requiring significant investments from both public and private players. By creating a cutting-edge AI model, this work tackles the crucial problems of EVs range prediction and charging optimization decisions. The contributions are summarized as the below: 1. Developed AI …

Iron Isotope Transformations In Saanich Inlet, Claire Onak

USF Tampa Graduate Theses and Dissertations

Iron (Fe) is required for many biogeochemical processes, with Fe bioavailability and chemistry being controlled by redox reactions that transform Fe between oxidation states and dissolved and particulate phases. In oxic seawater, Fe is present in the Fe(III) oxidation state, mainly as Fe oxyhydroxides. Under anoxic marine conditions, such as margin sediments under oxygen minimum zones or restricted basins with anoxic bottom water, Fe(III) is reduced to Fe(II), which is highly soluble and can be present at high concentrations ([Fe]). Fe isotope ratios (δ56Fe relative to IRMM-14) can be used to characterize Fe redox transformations, constrain Fe sources of Fe …

Modeling And Numerical Analysis Of The Cholesteric Landau-De Gennes Model, Andrew L. Hicks

LSU Doctoral Dissertations

This thesis gives an analysis of modeling and numerical issues in the Landau-de Gennes (LdG) model of nematic liquid crystals (LCs) with cholesteric effects. We derive various time-step restrictions for a (weighted) $L^2$ gradient flow scheme to be energy decreasing. Furthermore, we prove a mesh size restriction, for finite element discretizations, that is critical to avoid spurious numerical artifacts in discrete minimizers that is not well-known in the LC literature, particularly when simulating cholesteric LCs that exhibit ``twist''. Furthermore, we perform a computational exploration of the model and present several numerical simulations in 3-D, on both slab geometries and spherical …

Non-Native Rhizophora Mangle As Sinks For Coastal Contamination On Moloka’I, Hawai’I, Geoffrey Szafranski, Elise F. Granek, Michelle L. Hladik, Mia Hackett

Environmental Science and Management Faculty Publications and Presentations

Coastal mangrove forests provide a suite of environmental services, including sequestration of anthropogenic contamination. Yet, research lags on the environmental fate and potential human health risks of mangrove-sequestered contaminants in the context of mangrove removal for development and range shifts due to climate change. To address this, we conducted a study on Moloka'i, Hawai'i, comparing microplastic and pesticide contamination in coastal compartments both at areas modified by non-native red mangroves (Rhizophora mangle) and unmodified, open coastline. Sediment, porewater, and mangrove plant tissues were collected to quantify microplastic and pesticide concentrations across ecosystem type. Average microplastics were similar between …

Analytical Challenges In Omics Research On Asthma And Allergy: A National Institute Of Allergy And Infectious Diseases Workshop, Supinda Bunyavanich, Patrice M Becker, Matthew C Altman, Jessica Lasky-Su, Carole Ober, Karsten Zengler, Evgeny Berdyshev, Richard Bonneau, Talal Chatila, Nilanjan Chatterjee, Kian Fan Chung, Colleen Cutcliffe, Wendy Davidson, Gang Dong, Gang Fang, Patricia Fulkerson, Blanca E Himes, Liming Liang, Rasika A Mathias, Shuji Ogino, Joseph Petrosino, Nathan D Price, Eric Schadt, James Schofield, Max A Seibold, Hanno Steen, Lisa Wheatley, Hongmei Zhang, Alkis Togias, Kohei Hasegawa

Center for Medical Ethics and Health Policy Staff Publications

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes …

Influence Of Polymeric Microparticle Size And Loading Concentration On 3d Printing Accuracy And Degradation Behavior Of Composite Scaffolds, Gerry L Koons, Panayiotis D Kontoyiannis, Luis Diaz-Gomez, Selma Z Elsarrag, David W Scott, Mani Diba, Antonios G Mikos

Faculty, Staff and Students Publications

Successful employment of 3D printing for delivery of therapeutic biomolecules requires protection of their bioactivity on exposure to potentially inactivating conditions. Although intermediary encapsulation of the biomolecules in polymeric particulate delivery vehicles is a promising strategy for this objective, the inclusion of such particles in 3D printing formulations may critically impact the accuracy or precision of 3D printed scaffolds relative to their intended designed architectures, as well as the degradation behavior of both the scaffolds and the included particles. The present work aimed to elucidate the effect of poly(d,l-lactic-co-glycolic acid) particle size and loading concentration on material accuracy, …

Using Starling Murmuration As A Model For Creating A Global Health Community Of Practice To Advance Equity In Scholarship, Diane Nguyen, Rogers N Ssebunya, Kajal Hirani, Anna Mandalakas, Jennifer Benjamin, B Lee Ligon, Satid Thammasitboon

Faculty, Staff and Students Publications

Background: Disparities in scholarship exist between authors in low- or middle-income countries (LMIC) and high-income countries. Recognizing these disparities in our global network providing pediatric, adolescent, and maternal healthcare to vulnerable populations in LMIC, we sought to improve access and provide resources to address educational needs and ultimately impact the broader scholarship disparity.

Methods: We created a virtual community of practice (CoP) program underpinned by principles from starling murmuration to promote interdisciplinary scholarship. We developed guiding principles- autonomy, mastery and purpose- to direct the Global Health Scholarship Community of Practice Program. Program components included a continuing professional development (CPD) program, …

Phosphorylation Of Ryr2 Simultaneously Expands The Dyad And Rearranges The Tetramers, Parisa Asghari, David R L Scriven, Saba Shahrasebi, Hector H Valdivia, Katherina M Alsina, Carmen R Valdivia, J Alberto Navarro-Garcia, Xander H T Wehrens, Edwin D W Moore

Faculty, Staff and Students Publications

We have previously demonstrated that type II ryanodine receptors (RyR2) tetramers can be rapidly rearranged in response to a phosphorylation cocktail. The cocktail modified downstream targets indiscriminately, making it impossible to determine whether phosphorylation of RyR2 was an essential element of the response. Here, we used the β-agonist isoproterenol and mice homozygous for one of the following clinically relevant mutations: S2030A, S2808A, S2814A, or S2814D. We measured the length of the dyad using transmission electron microscopy (TEM) and directly visualized RyR2 distribution using dual-tilt electron tomography. We found that the S2814D mutation, by itself, significantly expanded the dyad and reorganized …

A Scoping Review Of Artificial Intelligence In Medical Education: Beme Guide No 84, Morris Gordon, Michelle Daniel, Aderonke Ajiboye, Hussein Uraiby, Nicole Y Xu, Rangana Bartlett, Janice Hanson, Mary Haas, Maxwell Spadafore, Ciaran Grafton-Clarke, Rayhan Yousef Gasiea, Colin Michie, Janet Corral, Brian Kwan, Diana Dolmans, Satid Thammasitboon

Faculty, Staff and Students Publications

Background: Artificial Intelligence (AI) is rapidly transforming healthcare, and there is a critical need for a nuanced understanding of how AI is reshaping teaching, learning, and educational practice in medical education. This review aimed to map the literature regarding AI applications in medical education, core areas of findings, potential candidates for formal systematic review and gaps for future research.

Methods: This rapid scoping review, conducted over 16 weeks, employed Arksey and O'Malley's framework and adhered to STORIES and BEME guidelines. A systematic and comprehensive search across PubMed/MEDLINE, EMBASE, and MedEdPublish was conducted without date or language restrictions. Publications included in …

Fluorescence Microscopy With Deep Uv, Near Uv, And Visible Excitation For In Situ Detection Of Microorganisms, Noel Case, Nikki Johnston, Jay Nadeau

Physics Faculty Publications and Presentations

We report a simple, inexpensive design of a fluorescence microscope with light-emitting diode (LED) excitation for detection of labeled and unlabeled microorganisms in mineral substrates. The use of deep UV (DUV) excitation with visible emission requires no specialized optics or slides and can be implemented easily and inexpensively using an oblique illumination geometry. DUV excitation (<280 >nm) is preferable to near UV (365 nm) for avoidance of mineral autofluorescence. When excited with DUV, unpigmented bacteria show two emission peaks: one in the near UV ∼320 nm, corresponding to proteins, and another peak in the blue to green range, corresponding to …