Statistics and Probability Commons^™

Ultraviolet Exposure And Photokeratitis Complaints Among Informal Welding Workers In Depok, West Java, Indonesia, Maria K I J Yustheresani, Fajaria Nurcandra, Azizah Musliha Fitri, Annisa Ika Putri, Dyah Utari

Kesmas

One of the photokeratitis risk factors is acute reversible radiation of ultraviolet (UV) rays, which injure the cornea's epithelial tissue. Informal welding workers are susceptible populations to UV rays exposure. This study aimed to confirm the influence of UV radiation exposure on photokeratitis complaints in welding workers in Cimanggis, Depok, West Java. A cross-sectional study was conducted from February to June 2019 and used to select 100 welding workers purposively. A semi-structured questionnaire was used to determine photokeratitis complaints, age, education level, eye protection, safety knowledge, and work period; the UV radiation measured by A UV meter. Data were analyzed …

Assessment Of Knowledge, Attitudes, And Behaviors Of Turkish Women On Breast And Cervical Cancer In Karabük Province, Turkey, Nergiz Sevinc, Belgin Oral, Burcu Korkut

Kesmas

Breast and cervical cancer incidence and mortality among women have been increasing worldwide. This cross-sectional study aimed to evaluate women's knowledge, attitudes, and behaviors regarding breast and cervical cancers. The sample was composed of 507 women aged 18 years and older who were admitted to a primary health care center in Karabük, Turkey, from October to December 2019. The data was obtained using a questionnaire consisting of 34 questions regarding participants’ socio demographic characteristics, knowledge, attitudes, and behaviors toward breast and cervical cancers. The mean age of the participants was 41.3±12.0 years and 68.4% of them were married. Slightly more …

Creating Optimal Conditions For Reproducible Data Analysis In R With ‘Fertile’, Audrey M. Bertin, Benjamin Baumer

Statistical and Data Sciences: Faculty Publications

The advancement of scientific knowledge increasingly depends on ensuring that data-driven research is reproducible: that two people with the same data obtain the same results. However, while the necessity of reproducibility is clear, there are significant behavioral and technical challenges that impede its widespread implementation and no clear consensus on standards of what constitutes reproducibility in published research. We present fertile, an R package that focuses on a series of common mistakes programmers make while conducting data science projects in R, primarily through the RStudio integrated development environment. fertile operates in two modes: proactively, to prevent reproducibility mistakes from happening …

An Analysis Of Growth Of The Community Integration Psychological Score In An Ethnically Diverse Population Experiencing Homelessness In A Permanent Supportive Housing Program Using Hierarchical Mixed Modeling, Leah Hollis Puglisi

Mathematics & Statistics ETDs

Hierarchical models are becoming increasingly common in epidemiological and psychological research. When analyzing data from such studies, the nested structure of the data must be taken into account. Mixed modeling in conjunction with hierarchical mixed modeling allows researchers to ask broad questions about the population of interest. Modeling under restricted maximum likelihood estimation (REML), as opposed to full maximum likelihood estimation (ML), increases the accuracy of estimates for the random effects in the model. We use hierarchical mixed modeling under REML estimation to analyze which factors increase “community integration”, a concept and a construct developed and used in the mental …

Data Analysis To Evaluate The Performance Of Breathing Masks Used For Filtering Nano-Level Particles At Manufacturing Sites, Gracia M. Dardano

Honors College Theses

The work performed in this research aims to evaluate the performance of commercially available breathing masks in filtering airborne nanoparticles at manufacturing sites. Nanoparticles are found virtually anywhere, from dust in a worksite to a simple sneeze. Therefore, they pose a substantial threat to human health as their velocity and volatility are high. This research analyzes if current efforts of breathing masks to hinder nanoparticles are effective, especially at manufacturing sites. Data has been collected in order to analyze the behavior of nanoparticles and to measure nanoparticle levels at manufacturing sites and its working environment. Data is statistical in nature …

A Bayesian Network Analysis Of The Human Exposure To Escherichia Coli Bacteria In The Environment, Brandon G. De Flon

Mathematics & Statistics ETDs

Diarrhea is a leading cause of death worldwide because a lack thereof in household sanitization exposes humans to high concentrations of pathogenic Escherichia coli. In 2016, the University of New Mexico’s Nepal Study Center collected cross-sectional survey data using proportional random sampling on three communities in Western Nepal. Structural and parameter learning estimation and approximate inference of Bayesian networks studied diarrheagenic E. coli exposure while incorporating participation in sanitary behaviors, access to sanitary built-in environments, and other human characteristics. Of the reported sickness, hand washing resulted in a 20 percent decrease, water treatment 8 percent, and both 28 percent. Of …

A Reflection Of Real Time Educational, Within-Subjects Data In Diverse Classrooms: One-Way Anova As A Solution To Data With Nonignorable Missingness And Skew, Amilynn N. Campa

Honors Program Theses and Research Projects

Schools across the United States and throughout the world administer tests to students to evaluate their academic performance. In many instances, however, especially in classrooms with higher populations of racial/ethnic minorities and low SES students, there are often missing scores, attributed to higher rates of absenteeism among these demographics (Callahan, 2019; Friedman-Krauss & Raver, 2015; Evans, 2004). When evaluating within subjects, longitudinal data, many will utilize a pre, post significance test such as a paired samples T test or a Repeated Measures ANOVA, however, due to the assumptions of these tests, missing data has posed a problem and requires data …

A Posteriori Error Estimates For Elliptic Eigenvalue Problems Using Auxiliary Subspace Techniques, Stefano Giani, Luka Grubišić, Harri Hakula, Jeffrey S. Ovall

Mathematics and Statistics Faculty Publications and Presentations

We propose an a posteriori error estimator for high-order p- or hp-finite element discretizations of selfadjoint linear elliptic eigenvalue problems that is appropriate for estimating the error in the approximation of an eigenvalue cluster and the corresponding invariant subspace. The estimator is based on the computation of approximate error functions in a space that complements the one in which the approximate eigenvectors were computed. These error functions are used to construct estimates of collective measures of error, such as the Hausdorff distance between the true and approximate clusters of eigenvalues, and the subspace gap between the corresponding true and approximate …

Viewing Ode Models Through A New Lens: The Generalized Linear Chain Trick, Paul Hurtado, Cameron Richards

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Stochastic Analysis And Statistical Inference For Seir Models Of Infectious Diseases, Andrés Ríos-Gutiérrez, Viswanathan Arunachalam, Anuj Mubayi

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Pharmacokinetics And Pharmacodynamics Models Of Tumor Growth And Anticancer Effects In Discrete Time, Ngoc Nguyen, Ferhan M. Atici

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Direct Questioning Of Sensitive Topics In Public Health Studies: A Simulation Study, Jessica K. Fox, Evrim Oral

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Study Of Sentiment Of Covid-19 Related Tweets In The Usa, Jack Luu, Rosangela Follmann

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Stochastic Modeling Of Ovarian Follicle Growth In Adult Female Rats, Zhaozhi Li

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

From Wave Propagation To Spin Dynamics: Mathematical And Computational Aspects, Oleksii Beznosov

Mathematics & Statistics ETDs

In this work we concentrate on two separate topics which pose certain numerical challenges. The first topic is the spin dynamics of electrons in high-energy circular accelerators. We introduce a stochastic differential equation framework to study spin depolarization and spin equilibrium. This framework allows the mathematical study of known equations and new equations modelling the spin distribution of an electron bunch. A spin distribution is governed by a so-called Bloch equation, which is a linear Fokker-Planck type PDE, in general posed in six dimensions. We propose three approaches to approximate solutions, using analytical and modern numerical techniques. We also present …

Profile Of Volatile Organic Compounds (Vocs) From Cold-Processed And Heat-Treated Virgin Coconut Oil (Vco) Samples, Ian Ken D. Dimzon, Grace B. Tantengco, Noel A. Oquendo, Fabian M. Dayrit

Chemistry Faculty Publications

Virgin coconut oil (VCO) can be prepared with or without heat. Fermentation and centrifuge processes can be done without the use of heat (cold process), while expelling involves heat due to friction. Volatile organic compounds (VOCs) from VCO samples prepared using these three methods were collected using solid phase microextraction (SPME) and analyzed using gas chromatography–mass spectrometry (GC-MS). Twenty-seven VCO samples from nine VCO producers were analyzed. The VOCs from refined, bleached, and deodorized coconut oil (RBDCO) were also obtained for comparison. Fourteen compounds were found to be common in more than 80% of the VCO samples analyzed. These included: …

New Proper Orthogonal Decomposition Approximation Theory For Pde Solution Data, Sarah Locke, John R. Singler

Mathematics and Statistics Faculty Research & Creative Works

In our previous work [J. R. Singler, SIAM J. Numer. Anal., 52 (2014), pp. 852- 876], we considered the proper orthogonal decomposition (POD) of time varying PDE solution data taking values in two different Hilbert spaces. We considered various POD projections of the data and obtained new results concerning POD projection errors and error bounds for POD reduced order models of PDEs. In this work, we improve on our earlier results concerning POD projections by extending to a more general framework that allows for nonorthogonal POD projections and seminorms. We obtain new exact error formulas and convergence results for POD …

Evidence Of Nickel And Other Trace Elements And Their Relationship To Clinical Findings In Acute Mesoamerican Nephropathy: A Case-Control Analysis, Rebecca S. B. Fischer, Jason M. Unrine, Chandan Vangala, Wayne T. Sanderson, Sreedhar Mandayam, Kristy O. Murray

Plant and Soil Sciences Faculty Publications

BACKGROUND: Although there are several hypothesized etiologies of Mesoamerican Nephropathy (MeN), evidence has not yet pointed to the underlying cause. Exposure to various trace elements can cause the clinical features observed in MeN.

METHODS AND FINDINGS: We measured 15 trace elements, including heavy metals, in renal case-patients (n = 18) and healthy controls (n = 36) in a MeN high-risk region of Nicaragua. Toenails clippings from study participants were analyzed using inductively coupled plasma mass spectrometry. A case-control analysis was performed, and concentrations were also analyzed over participant characteristics and clinical parameters. Nickel (Ni) concentrations were significantly higher in toenails …

Multimodal Data Fusion And Attack Detection In Recommender Systems, Mehmet Aktukmak

USF Tampa Graduate Theses and Dissertations

The commercial platforms that use recommender systems can collect relevant information to produce useful recommendations to the platform users. However, these sources usually contain missing values, imbalanced and heterogeneous data, and noisy observations. Such characteristics render the process of exploiting the information nontrivial, as one should carefully address them during the data fusion process. In addition to the degenerative characteristics, some entries can be fake, i.e., they can be the outcomes of malicious intents to manipulate the system. These entries should be eliminated before incorporation to any recommendation task. Detecting such malicious attacks quickly and accurately and then mitigating them …

Implementation And Sustainment Of A Statewide Telemedicine Diabetic Retinopathy Screening Network For Federally Designated Safety-Net Clinics, Ana Bastos De Carvalho, S. Lee Ware, Feitong Lei, Heather M. Bush, Robert Sprang, Eric B. Higgins

Ophthalmology and Visual Science Faculty Publications

CONTEXT: Diabetic retinopathy (DR) is the leading cause of incident blindness among working-age adults in the United States. Federally designated safety-net clinics (FDSC) often serve as point-of-contact for patients least likely to receive recommended DR screenings, creating opportunity for targeted interventions to increase screening access and compliance.

STUDY DESIGN AND METHODS: With such a goal, we implemented and assessed the longitudinal performance of an FDSC-based telemedicine DR screening (TDRS) network of 22 clinical sites providing nonmydriatic fundus photography with remote interpretation and reporting. Retrospective analysis of patient encounters between February 2014 and January 2019 was performed to assess rates of …

Cash Flow Forecasting Using Probabilistic Neural Networks, Marwan Ashour

Journal of the Arab American University مجلة الجامعة العربية الامريكية للبحوث

This paper aimed to compare the modern methods of cash flow forecasting with the traditional ones. In other words, the researcher compared between the Probabilistic Neural Networks and Transfer Function. It is worth mentioning that cash flow forecasting , nowadays, is very important and helps the upper management plan, control, assess the performance and make decisions. More specifically, in this paper, the Artificial Neural networks were used to diagnose the nature of the cash flow for the next period of time and then forecast the cash flow. The experiment was conducted in The General company for Electricity Distribution in Baghdad. …

Blood Pressure Monitoring Following Individual Carpules Of Anesthetic Utilizing Computer-Controlled Anesthetic Delivery, Kristi M. Soileau, Adam E. Degenova, Qingzhao Yu

School of Dentistry Faculty Publications

To date, no study has evaluated blood pressure following administration of each carpule given for dental procedures using a computerized dental anesthesia system. Blood pressures taken prior to performing invasive periodontal procedures were compared with those readings measured following delivery of each of up to three consecutive carpules of Marcaine or Xylocaine in varying order. Pressure differences were also adjusted for age, sex, race, and whether a prescribed anxiolytic was taken beforehand. Neither systolic nor diastolic blood pressures changed significantly as compared to initial blood pressure readings. However, compared with Whites, Hispanics, and Middle Easterners, Blacks had significantly higher systolic …

A Natural Frenet Frame For Null Curves On The Lightlike Cone In Minkowski Space ℝ⁴₂, Nemat Abazari, Martin Bohner, Ilgin Sağer, Alireza Sedaghatdoost, Yusuf Yayli

Mathematics and Statistics Faculty Research & Creative Works

In this paper, we investigate the representation of curves on the lightlike cone ℚ³₂ in Minkowski space ℝ⁴₂ by structure functions. In addition, with this representation, we classify all of the null curves on the lightlike cone ℚ³₂ in four types, and we obtain a natural Frenet frame for these null curves. Furthermore, for this natural Frenet frame, we calculate curvature functions of a null curve, especially the curvature function κ₂ = 0 , and we show that any null curve on the lightlike cone is a helix. Finally, we find all curves with constant curvature functions.

Analyzing Yankees And Red Sox Sentiment Over The Course Of A Season, Connor Koch

Honors Projects in Data Science

This paper investigates data collected on twitter which references the Yankees or Red Sox during the 2020 Major League Baseball (MLB) season. The objective is to analyze the sentiment of tweets referencing the Yankees and Red Sox over the course of the season. In addition, an investigation of the networks within the data and the topics that were prevalent will be conducted. The 2020 MLB season was started late because of the COVID-19 pandemic and was a season like no other. The expectation of a dataset revolving around baseball is that the topics discussed would be about baseball. The findings …

Stirring The Pot: Switching From Blended Fee-For-Service To Blended Capitation Models Of Physician Remuneration., Nibene H Somé, Rose Anne Devlin, Nirav Mehta, Gregory S Zaric, Sisira Sarma

Epidemiology and Biostatistics Publications

In Canada's most populous province, Ontario, family physicians may choose between the blended fee-for-service (Family Health Group [FHG]) and blended capitation (Family Health Organization [FHO] payment models). Both models incentivize physicians to provide after-hours (AH) and comprehensive care, but FHO physicians receive a capitation payment per enrolled patient adjusted for age and sex, plus a reduced fee-for-service while FHG physicians are paid by fee-for-service. We develop a theoretical model of physician labor supply with multitasking to predict their behavior under FHG and FHO, and estimable equations are derived to test the predictions empirically. Using health administrative data from 2006 to …

Distinct Clinicopathologic Clusters Of Persons With Tdp-43 Proteinopathy, Yuriko Katsumata, Erin L. Abner, Shama Karanth, Merilee A. Teylan, Charles N. Mock, Matthew D. Cykowski, Edward B. Lee, Kevin L. Boehme, Shubhabrata Mukherjee, John S. K. Kauwe, Richard J. Kryscio, Frederick A. Schmitt, David W. Fardo, Peter T. Nelson

Biostatistics Faculty Publications

To better understand clinical and neuropathological features of TDP-43 proteinopathies, data were analyzed from autopsied research volunteers who were followed in the National Alzheimer’s Coordinating Center (NACC) data set. All subjects (n = 495) had autopsy-proven TDP-43 proteinopathy as an inclusion criterion. Subjects underwent comprehensive longitudinal clinical evaluations yearly for 6.9 years before death on average. We tested whether an unsupervised clustering algorithm could detect coherent groups of TDP-43 immunopositive cases based on age at death and extensive neuropathologic data. Although many of the brains had mixed pathologies, four discernible clusters were identified. Key differentiating features were age at …

Invited Article By M. Gidea Extreme Events And Emergency Scales, Veniamin Smirnov, Zhuanzhuan Ma, Dimitri Volchenkov

School of Mathematical & Statistical Sciences Faculty Publications

An event is extreme if its magnitude exceeds the threshold. A choice of a threshold is subject to uncertainty caused by a method, the size of available data, a hypothesis on statistics, etc. We assess the degree of uncertainty by the Shannon's entropy calculated on the probability that the threshold changes at any given time. If the amount of data is not sufficient, an observer is in the state of Lewis Carroll's Red Queen who said "When you say hill, I could show you hills, in comparison with which you'd call that a valley". If we have enough data, the …

A Statistical Learning Regression Model Utilized To Determine Predictive Factors Of Social Distancing During Covid-19 Pandemic, Timothy A. Smith, Albert J. Boquet, Matthew V. Chin

Publications

In an application of the mathematical theory of statistics, predictive regression modelling can be used to determine if there is a trend to predict the response variable of social distancing in terms of multiple predictor input “predictor” variables. In this study the social distancing is measured as the percentage reduction in average mobility by GPS records, and the mathematical results obtained are interpreted to determine what factors drive that response. This study was done on county level data from the state of Florida during the COVID-19 pandemic, and it is found that the most deterministic predictors are county population density …

The Use Of Penalized Regression Analysis To Identify County-Level Demographic And Socioeconomic Variables Predictive Of Increased Covid-19 Cumulative Case Rates In The State Of Georgia, Holly L. Richmond, Joana Tome, Haresh Rochani, Isaac Chun-Hai Fung, Gulzar H. Shah, Jessica S. Schwind

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Systemic inequity concerning the social determinants of health has been known to affect morbidity and mortality for decades. Significant attention has focused on the individual-level demographic and co-morbid factors associated with rates and mortality of COVID-19. However, less attention has been given to the county-level social determinants of health that are the main drivers of health inequities. To identify the degree to which social determinants of health predict COVID-19 cumulative case rates at the county-level in Georgia, we performed a sequential, cross-sectional ecologic analysis using a diverse set of socioeconomic and demographic variables. Lasso regression was used to identify variables …

Multi-Ancestry Genome-Wide Association Study Accounting For Gene-Psychosocial Factor Interactions Identifies Novel Loci For Blood Pressure Traits, Daokun Sun, Melissa A. Richard, Soloman K. Musani, Yun Ju Sung, Thomas W. Winkler, Karen Schwander, Jin Fang Chai, Xiuqing Guo, Tuomas O. Kilpeläinen, Dina Vojinovic, Hugues Aschard, Traci M. Bartz, Lawrence F. Bielak, Michael R. Brown, Kumaraswamy Chitrala, Fernando P. Hartwig, Andrea R. V. R. Horimoto, Yongmei Liu, Alisa K. Manning, Raymond Noordam, Donna K. Arnett

Epidemiology and Environmental Health Faculty Publications

Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP, taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from five ancestry groups. In the combined meta-analyses of stages 1 and 2, we identified 59 loci (p value < 5e−8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (PLCL2), synaptic function and neurotransmission (LIN7A …