Digital Commons Network^™

Oral, Cardiovascular And Respiratory Effects Of E-Cigarettes: Synthesis Of Literature, Nareh Eshgian

Annual Research Symposium

No abstract provided.

Adversarial And Data Poisoning Attacks Against Deep Learning, Jing Lin

USF Tampa Graduate Theses and Dissertations

Machine translation software, image captioning, grammar check (Grammarly), chatbot, real-time captioning and translation, music genre classification, and document classification are a few examples of deep learning applications that achieve outstanding performance in areas where traditional statistical techniques have difficulty performing classification and/or regression. Google translator has over 100 billion daily users and can translate 109 languages instantly (much faster than a human translator). AlphaGo won Lee Sedol, the eighteen-time world champion. Microsoft Team's living captioning provides accurate real-time captioning as a speaker speaks. Deep learning achieves undoubtedly remarkable performance. However, recent studies on adversarial attacks and data poisoning attacks show …

Application And Efficacy Of Color-Coded Learning Models, Parker Grossman

Annual Research Symposium

No abstract provided.

Covid-19 Ramifications And Effects, Landon Ledingham

Annual Research Symposium

No abstract provided.

Evaluation On Appropriateness Of Fluoroquinolone Use In An Acute Care Hospital, Cynthia Huang

Annual Research Symposium

No abstract provided.

Covid-19 Variant, Vaccine And Booster, Manas Mandal

Annual Research Symposium

No abstract provided.

Rna Sequencing Reveals That Cyp3a5 Sirna Treatment Induces Cell Cycle Blockade And Senescence In Mdapca2b Human Prostate Cancer Cells, Jeetesh Sharma

Annual Research Symposium

No abstract provided.

Evaluation Of Appropriate Initiation And De-Escalation Of Piperacillin-Tazobactam In Hospitalized Patients At An Acute Care Hospital, Ivy Yang

Annual Research Symposium

No abstract provided.

Student Perception On The Implementation Of An End-Of-The-Day Quiz And Its Impact On Student Learning And Class Attendance In A Three-Year Accelerated Doctorate Program Of Pharmacy., Desiree Chong, Jousef Alandy0dy, Arup Chakraborty

Annual Research Symposium

No abstract provided.

Participation In Curriculum And Cultural Ambassador Group To Enhance Student Belongingness, Jake Tuft, Jacob Schvaneveldt

Annual Research Symposium

COVID-19 negatively impacted students' abilities to participate in live, in-person events; students were unable to interact with peers or build relationships critical to success and well-being. Quarantine, social distancing and video conferencing did not create this problem however, it simply amplified the fact that dental students seemingly lack camaraderie and a sense of belongingness. The Curriculum and Cultural Ambassador group was created to allow students to bond over shared goals in the hopes of improving their experiences within dental school. This group gives students the ability to “Be the Change” on campus and enact real-time change to foster a sense …

A Standardized Approach To Blood Pressure Training In First-Year Medical Students, Andrew Romney

Annual Research Symposium

No abstract provided.

Succinic Semialdehyde Dehydrogenase Deficiency (Ssadhd): Qualitative Needs Assessment For Patients With A Rare Neurological Disorder, Cassandra Bovee, Kayla Woodring

Annual Research Symposium

No abstract provided.

Identifying Bias In Healthcare And Creating Intervention Strategies At Colleges Of Medicine And Other Healthcare Professions, Cameron Chalmers, Emmanuel Oyalabu

Annual Research Symposium

No abstract provided.

Identification Of Gsk-3 Beta Inhibitors From Natural Products, Vincent Anella, Tyler Rose

Annual Research Symposium

No abstract provided.

Evaluation Of The Neurogenic And Dentinogenic Effect Of Valproic Acid On Undifferentiated Mesenchymal Cells Of Human Dental Pulp, Edward Yeates

Annual Research Symposium

No abstract provided.

Comparing The Efficacy Of Sodium Fluoride And Silver Diamine Fluoride In Arresting Caries Through Statistical Analysis, Elana Ferris

Annual Research Symposium

No abstract provided.

Depression And Factors Impacting Quality Of Life Among Adults With Asthma Presence In Nevada, Elizabeth D. Kahane, Lung-Chang Chien, Brian Labus, Dharini M. Bhammar, Jocy-Anna Chevalier, Sheniz Moonie

Epidemiology & Biostatistics Faculty Research

Background: Asthma, a chronic, non-communicable disease has been shown to negatively affect mental health and quality of life among adults. Annually approximately 8% of adult Nevadans report current asthma symptoms and 12.6% report having a lifetime diagnosis. The purpose of this study was to evaluate the association between asthma and depression and explore quality of life factors affecting adult Nevadans with asthma. Methods: Using behavioral risk factor surveillance system (BRFSS) data, this study evaluated the association between self-reported asthma and depression in Nevada using weighted multiple logistic regression. BRFSS asthma call-back survey (ACBS) data were used to determine the frequency …

A Physically Constrained Wavelet-Aided Statistical Model (Pcwasm) For Multidecadal Groundwater Dynamics Predictions And Climate Change Evaluation, Fatih Gordu

USF Tampa Graduate Theses and Dissertations

Long-term groundwater management relies on forecasts of decadal or longer groundwater levels driven by nested scales of variability in climate. Discerning the impacts of anthropogenic stressors on groundwater is also critical for establishing predevelopment benchmark groundwater conditions and developing climate change adaptation strategies to reduce risks and increase resiliency. This research demonstrates the development and successful applications of a new methodology to predict and assess multidecadal groundwater dynamics for understanding long-term effects of climate change and groundwater withdrawals.

A Physically Constrained Wavelet-Aided Statistical Model (PCWASM) is first introduced to analyze and predict monthly aquifer levels on multidecadal time scales. The …

Comparative Analysis Of Trends In American Physics Education, Adam Tyler Crank

Honors Capstone Projects and Theses

No abstract provided.

Television Viewing Time And All-Cause Mortality: Interactions With Bmi, Physical Activity, Smoking, And Dietary Factors, Christopher T. Swain, Julie K. Bassett, Allison M. Hodge, David W. Dunstan, Neville Owen, Yi Yang, Harindra Jayasekara, James R. Hébert Scd, Nitin Shivappa Mbbs, Mph, Ph.D., Robert J. Macinnis, Roger L. Milne, Dallas R. English, Brigid M. Lynch

Faculty Publications

Background Higher levels of time spent sitting (sedentary behavior) contribute to adverse health outcomes, including earlier death. This effect may be modified by other lifestyle factors. We examined the association of television viewing (TV), a common leisure-time sedentary behavior, with all-cause mortality, and whether this is modified by body mass index (BMI), physical activity, smoking, alcohol intake, soft drink consumption, or diet-associated inflammation. Methods Using data from participants in the Melbourne Collaborative Cohort Study, flexible parametric survival models assessed the time-dependent association of self-reported TV time (three categories: < 2 h/day, 2-3 h/day, > 3 h/day) with all-cause mortality. Interaction terms were fitted to test whether …

Using Fine-Scale Aquatic Habitat Data To Construct Dreissenid Sdms In The Laurentian Great Lakes, Grace C. Henderson

USF Tampa Graduate Theses and Dissertations

The invasion of the Laurentian Great Lakes by aquatic invasive species (AIS) has been the subject of investigation for decades, due to their dramatic alterations to the ecosystem and high economic costs. Two AIS with the largest impacts are dreissenid zebra and quagga mussels, and though these species have been studied extensively, questions remain about what factors control their distributions, and whether lake warming will alter these distributions. Species distribution models (SDMs) offer a powerful tool to examine the relationship between species presences and environmental variables, which are typically bioclimactic data. The creation of the Aquatic Habitat (AqHab) dataset containing …

Measurements Of Generalizability And Adjustment For Bias In Clinical Trials, Yuanyuan Lu

USF Tampa Graduate Theses and Dissertations

While randomized controlled trials (RCTs) are widely used as a gold standard in clinical research and public health, they are criticized because of a potential lack of generalizability, as the trial patients may be unrepresentative of the target patient population. Few research addresses how to assess and evaluate the generalizability of RCTs. As we know, patients are rarely selected on a random basis from a well-defined patient population of interest into a clinical trial. Generalizing findings from the RCT samples to the patient population has begun to receive increasing attention. We simulate a patient population with treatment effect size of …

Effective Statistical And Machine Learning Methods To Analyze Children's Vocabulary Learning, Houston T. Sanders

USF Tampa Graduate Theses and Dissertations

Poor methodological and statistical practices can lead to unreliable results. The collaboration between statisticians and researchers can remedy this. Early education intervention research rarely uses advanced statistical techniques. Within early education, vocabulary instruction has been well-studied, yet outcomes continue to be underwhelming. The specialized knowledge and expertise statisticians possess has the potential to enhance word learning research by applying sophisticated analyses not commonly used. Choosing vocabulary words for instruction can be a daunting task and is highly subjective. In an effort to aid in the selection process, researchers use a word selection framework that groups words into three tiers. Even …

Split Classification Model For Complex Clustered Data, Katherine Gerot

Honors Program: Senior Projects (Public)

Classification in high-dimensional data has generated tremendous interest in a multitude of fields. Data in higher dimensions often tend to reside in non-Euclidean metric space. This prevents Euclidean-based classification methodologies, such as regression, from reliably modeling the data. Many proposed models rely on computationally-complex embedding to convert the data to a more usable format. Others, namely the Support Vector Machine, rely on kernel manipulation to implicitly describe the "feature space" to arrive at a non-linear decision boundary. The proposed methodology in this paper seeks to classify complex data in a relatively computationally-simple and explainable manner.

Use Of Machine Learning Approaches And Statistical Techniques To Adjust For Nonadherence In Randomized Clinical Trials., Andrew G Chapple

School of Public Health Faculty Publications

No abstract provided.

Determinants Of Covid-19 Vaccinations Among A State-Wide Year-Long Surveillance Initiative In A Conservative Southern State, Lídia Gual-Gonzalez, Maggie S.J. Mccarter, Kyndall Dye-Braumuller, Stella Self, Connor H. Ross, Chloe Rodriguez-Ramos, Virginie G. Daguise, Melissa Nolan Ph.D., Mph

Faculty Publications

By the end of 2021, the COVID-19 pandemic resulted in over 54 million cases and more than 800,000 deaths in the United States, and over 350 million cases and more than 5 million deaths worldwide. The uniqueness and gravity of this pandemic have been reflected in the public health guidelines poorly received by a growing subset of the United States population. These poorly received guidelines, including vaccine receipt, are a highly complex psychosocial issue, and have impacted the successful prevention of disease spread. Given the intricate nature of this important barrier, any single statistical analysis methodologically fails to address all …

Team Coordination Dynamics Of Winning Nba Teams, Alli Grunkemeyer, Joel H. Sommerfeld

UNO Student Research and Creative Activity Fair

Predicting sports games outcomes is an endless pursuit shared by stakeholders ranging from fans to coaches to data scientists. We have begun investigating the value of positional data recorded during basketball gameplay with the goal of predicting outcomes from team dynamics as they emerge. We approached this problem by analyzing the “shape” of team movements on the court and investigated whether team dynamics in NBA games mimicked long-range correlated patterns observed in other team contexts. We analyzed 622 NBA games from an archival data set, including all area time series obtained for each of the four quarters. We fit a …

Cellular Dna Effects Of Radiation And Cancer Risk Assessment In Cells With Mitochondrial Defects, J. Chen, D. M. Sridharan, C. L. Cross, J. M. Pluth

Epidemiology & Biostatistics Faculty Research

Mitochondria play a key role in mediating non-targeted effects (NTE) post-radiation exposure. Mitochondrial DNA (mtDNA), due to its less efficient repair as compared to nuclear DNA, is more severely affected by radiation exposure and mutations in essential mtDNA genes can further exacerbate oxidative stress. Our objective was to evaluate the impact of mitochondrial defects on radiation-induced DDR and genomic instability, biomarkers that can foreshadow cancer development. To better understand this relationship, we used commercially available lymphoblastoid cell lines containing characterized mitochondrial mutations and studied the kinetics of DNA damage and relative telomere length (RTL) changes over time post 0.5 Gy …

Death-Related Anxiety Associated With Riskier Decision-Making Irrespective Of Framing: A Bayesian Model Comparison, Blaine Tomkins

Psychology Faculty Publications

A commonly reported finding is that anxious individuals are less likely to make risky decisions. However, no studies have examined whether this association extends to death-related anxiety. The present study examined how groups low, moderate, and high in death-related anxiety make decisions with varying levels of risk. Participants completed a series of hypothetical bets in which the probability of a win was systematically manipulated. High-anxiety individuals displayed the greatest risk-taking behavior, followed by the moderate-anxiety group, with the low-anxiety group being most risk-averse. Experiment 2 tested this association further by framing outcomes in terms of losses, rather than gains. A …

Experimental Design On High-Speed Sliding Wear, Irene D. Liew

Theses and Dissertations

The purpose of this research is to develop, conduct, and analyze an experimental design that characterizes wear rates of various materials sliding at high speeds along AISI 4340 steel. This work is in support of Holloman Air Force Base, which is invested in engineering a more wear-resistant rocket slipper for its high-speed test track. This research uses a design of experiments approach to systematically identify and evaluate potential slipper attributes that mitigate wear according to a heat transfer model. Final findings include recommendations of slipper materials that theoretically perform similar to or better than the baseline Vascomax®C300 maraging steel material. …