Digital Commons Network^™

The Beverton-Hold Model On Isolated Time Scales, Martin Bohner, Jaqueline Mesquita, Sabrina Streipert

Mathematics and Statistics Faculty Research & Creative Works

In this work, we formulate the Beverton-Holt model on isolated time scales and extend existing results known in the discrete and quantum calculus cases. Applying a recently introduced definition of periodicity for arbitrary isolated time scales, we discuss the effects of periodicity onto a population modeled by a dynamic version of the Beverton-Holt equation. The first main theorem provides conditions for the existence of a unique !-periodic solution that is globally asymptotically stable, which addresses the first Cushing-Henson conjecture on isolated time scales. The second main theorem concerns the generalization of the second Cushing-Henson conjecture. It investigates the effects of …

Optimal Equivalence Testing In Exponential Families, Renren Zhao, Robert L. Paige

Mathematics and Statistics Faculty Research & Creative Works

We develop uniformly most powerful unbiased (UMPU) two sample equivalence test for a difference of canonical parameters in exponential families. This development involves a non-unique reparameterization. We address this issue via a novel characterization of all possible reparameterizations of interest in terms of a matrix group. Furthermore, our procedure involves an intractable conditional distribution which we reproduce to a high degree of accuracy using saddle point approximations. The development of this saddle point-based procedure involves a non-unique reparameterization, but we show that our procedure is invariant under choice of reparameterization. Our real data example considers the mean-to-variance ratio for normally …

On The Hartogs Extension Theorem For Unbounded Domains In CN, Al Boggess, Roman Dwilewicz, Egmont Porten

Mathematics and Statistics Faculty Research & Creative Works

Let Ω ⊂ Cn, n > 2, be a domain with smooth connected boundary. If Ω is relatively compact, the Hartogs–Bochner theorem ensures that every CR distribution on ∂Ω has a holomorphic extension to Ω. For unbounded domains this extension property may fail, for example if Ω contains a complex hypersurface. The main result in this paper tells that the extension property holds if and only if the envelope of holomorphy of Cn \ Ω is Cn. It seems that it is the first result in the literature which gives a geometric characterization of unbounded domains in Cn for which the …

Fundamental Structure Of General Stochastic Dynamical Systems: High-Dimension Case, Haoyu Wang, Xiaoliang Gan, Wenqing Hu, Ping Ao

Mathematics and Statistics Faculty Research & Creative Works

No one has proved that mathematically general stochastic dynamical systems have a special structure. Thus, we introduce a structure of a general stochastic dynamical system. According to scientific understanding, we assert that its deterministic part can be decomposed into three significant parts: the gradient of the potential function, friction matrix and Lorenz matrix. Our previous work proved this structure for the low-dimension case. In this paper, we prove this structure for the high-dimension case. Hence, this structure of general stochastic dynamical systems is fundamental.

Nonlinear Mixed-Effects Models For Hiv Viral Load Trajectories Before And After Antiretroviral Therapy Interruption, Incorporating Left Censoring, Sihaoyu Gao, Lang Wu, Tingting Yu, Roger Kouyos, Huldrych F. Gunthard, Rui Wang

Harvard University Biostatistics Working Paper Series

Characterizing features of the viral rebound trajectories and identifying host, virological, and immunological factors that are predictive of the viral rebound trajectories are central to HIV cure research. In this paper, we investigate if key features of HIV viral decay and CD4 trajectories during antiretroviral therapy (ART) are associated with characteristics of HIV viral rebound following ART interruption. Nonlinear mixed effect (NLME) models are used to model viral load trajectories before and following ART interruption, incorporating left censoring due to lower detection limits of viral load assays. A stochastic approximation EM (SAEM) algorithm is used for parameter estimation and inference. …

Asymptotic Properties Of Kneser Solutions To Third-Order Delay Differential Equations, Martin Bohner, John R. Graef, Irena Jadlovská

Mathematics and Statistics Faculty Research & Creative Works

The aim of this paper is to extend and complete the recent work by Graef et al. (J. Appl. Anal. Comput., 2021) analyzing the asymptotic properties of solutions to third-order linear delay differential equations. Most importantly, the authors tackle a particularly challenging problem of obtaining lower estimates for Kneser-type solutions. This allows improvement of existing conditions for the nonexistence of such solutions. As a result, a new criterion for oscillation of all solutions of the equation studied is established.

A Survey On The Use Of Plastic Versus Biodegradable Bottles For Drinking Water Packaging In The United Arab Emirates, Himadri Rajput, Munjed A. Maraqa, Fatima Zraydi, Lina A. Al Khatib, Noor Ameen, Rime Ben Elkaid, Safia S. Al Jaberi, Noura A. Alharbi, Reka Howard, Ashraf Aly Hassan

Department of Statistics: Faculty Publications

Due to intensive utilization and extensive production, plastic waste is becoming a serious threat to the environment and human health. The situation is even worse in countries such as the United Arab Emirates (UAE), where single-use plastic water bottles add to the load of plastic pollution. The main objective of this survey was to assess the extent of bottled water utilization by the UAE residents and their awareness of the environmental concerns arising from single-use plastic bottles. The aim was also to evaluate their willingness to shift towards using biodegradable plastic bottles. This study involved the feedback of 2589 respondents …

Seasonal Variation In Terrestrial Invertebrate Subsidies To Tropical Streams And Implications For The Feeding Ecology Of Hart’S Rivulus (Anablepsoides Hartii), David C. Owens, Thomas N. Heatherly, Kent M. Eskridge, Colden V. Baxter, Steven A. Thomas

Department of Statistics: Faculty Publications

Terrestrial invertebrates are important subsidies to fish diets, though their seasonal dynamics and importance to tropical stream consumers are particularly understudied. In this year-round study of terrestrial invertebrate input to two Trinidadian headwater streams with different forest canopy densities, we sought to (a) measure the mass and composition of terrestrial inputs with fall-in traps to evaluate the influences of seasonality, canopy cover, and rainfall intensity, and; (b) compare terrestrial and benthic prey importance to Anablepsoides hartii(Hart’s Rivulus), the dominant invertivorous fish in these streams, by concurrently measuring benthic and drifting invertebrate standing stocks and the volume and composition of …

Cranberry Polyphenols In Esophageal Cancer Inhibition: New Insights, Katherine M. Weh, Yun Zhang, Connor L. Howard, Amy B. Howell, Jennifer L. Clarke, Laura A. Kresty

Department of Statistics: Faculty Publications

Esophageal adenocarcinoma (EAC) is a cancer characterized by rapidly rising incidence and poor survival, resulting in the need for new prevention and treatment options. We utilized two cranberry polyphenol extracts, one proanthocyanidin enriched (C-PAC) and a combination of anthocyanins, flavonoids, and glycosides (AFG) to assess inhibitory mechanisms utilizing premalignant Barrett’s esophagus (BE) and EAC derived cell lines. We employed reverse phase protein arrays (RPPA) and Western blots to examine cancer-associated pathways and specific signaling cascades modulated by C-PAC or AFG. Viability results show that C-PAC is more potent than AFG at inducing cell death in BE and EAC cell lines. …

Genome-Wide Association Study Of Disease Resilience Traits From A Natural Polymicrobial Disease Challenge Model In Pigs Identifies The Importance Of The Major Histocompatibility Complex Region, Jian Cheng, Rohan Fernando, Hao Cheng, Stephen D. Kachman, Kyusang Lim, John C.S. Harding, Michael K. Dyck, Frederic Fortin, Graham S. Plastow, Piggen Canada Research Consortium, Jack C.M. Dekkers

Department of Statistics: Faculty Publications

Infectious diseases cause tremendous financial losses in the pork industry, emphasizing the importance of disease resilience, which is the ability of an animal to maintain performance under disease. Previously, a natural polymicrobial disease challenge model was established, in which pigs were challenged in the late nursery phase by multiple pathogens to maximize expression of genetic differences in disease resilience. Genetic analysis found that performance traits in this model, including growth rate, feed and water intake, and carcass traits, as well as clinical disease phenotypes, were heritable and could be selected for to increase disease resilience of pigs. The objectives of …

Kryging: Geostatistical Analysis Of Large-Scale Datasets Using Krylov Subspace Methods, Suman Majumder, Yawen Guan, Brian J. Reich, Arvind K. Saibaba

Department of Statistics: Faculty Publications

Analyzing massive spatial datasets using a Gaussian process model poses computational challenges. This is a problem prevailing heavily in applications such as environmental modeling, ecology, forestry and environmental health. We present a novel approximate inference methodology that uses profile likelihood and Krylov subspace methods to estimate the spatial covariance parameters and makes spatial predictions with uncertainty quantification for point-referenced spatial data. The proposed method, Kryging, applies for both observations on regular grid and irregularly-spaced observations, and for any Gaussian process with a stationary isotropic (and certain geometrically anisotropic) covariance function, including the popular Matérn covariance family. We make use of …

Expanding The Network Evaluation Toolkit: Combining Social Network Analysis & Qualitative Comparative Analysis, Debbie Gowensmith

Electronic Theses and Dissertations

Collective action networks are complex systems of interrelated individuals or groups that come together for a common social change purpose (Ernstson, 2011). Researchers have used social network analysis (SNA) to examine the relationship structures and characteristics of collective action networks. However, determining whether collective action networking produces outcomes has been challenging because networks are complex, affected by context, and produce interdependent data. I addressed these challenges by pairing SNA with qualitative comparative analysis (QCA), a configurational comparative method. Using QCA, researchers can tease out which conditions are necessary or sufficient to produce an outcome. I analyzed a collective action network …

Using The Fraction Of Missing Information (Fmi) In Selecting Auxiliary Variables To Impute Missingness In Confirmatory Factor Analysis (Cfa), Dareen Taha Alzahrani

Electronic Theses and Dissertations

This study aimed to investigate the effectiveness of using the fraction of missing information (FMI) to select auxiliary variables in imputing missing data in confirmatory factor analysis (CFA). This was done by conducting two studies (a simulation study and an empirical study). A Monte Carlo simulation technique was used to compare the performance and the effect of the restrictive strategy based on FMI and the inclusive strategy on parameter estimate bias and parameter estimate efficiency. The missing data mechanisms, missing data proportion, correlation strength between the analysis variables and auxiliary variables, and the inclusive and restrictive strategies were assessed in …

Examining The Credibility Of Story-Based Causal Methodologies, Megan E. Kauffmann

Electronic Theses and Dissertations

The purpose of this study was to explore how evaluators justify using story-based methodologies when examining causality. The two primary research questions of the study included: 1) what arguments are made by evaluators to justify the credibility of story-based causal methodologies to evaluation stakeholders; and 2) from the perspective of evaluators, how do contextual factors influence whether story-based causal methodologies are perceived as credible by evaluation stakeholders? A case study was conducted to examine the cases of four evaluators who had experience implementing a story-based methodology in an evaluation. Data collection procedures included two interviews with each participant and a …

Mis-Specification Of Functional Forms In Growth Mixture Modeling: A Monte Carlo Simulation, Richa Ghevarghese

Electronic Theses and Dissertations

Growth mixture modeling (GMM) is a methodological tool used to represent heterogeneity in longitudinal datasets through the identification of unobserved subgroups following qualitatively and quantitatively distinct trajectories in a population. These growth trajectories or functional forms are informed by the underlying developmental theory, are distinct to each subgroup, and form the core assumptions of the model. Therefore, the accuracy of the assumed functional forms of growth strongly influences substantive research and theories of growth. While there is evidence of mis-specified functional forms of growth in GMM literature, the weight of this violation has been largely overlooked. Current solutions to circumvent …

Guide To The Dr. L.S. Dederick Papers, 1908-1956, Undated, Orson Kingsley, Patrick Koetsch

Archives & Special Collections Finding Aids

Louis Serle (L.S.) Dederick was born in Chicago in 1883. He received his Ph.D. in Mathematics from Harvard University in 1909. From 1909 – 1917 he was a professor at Princeton University. From 1917 – 1924 he was professor at the U.S. Naval Academy in Annapolis, Maryland. In 1926 Dederick began working for the U.S. Army, Ordnance. During his time there he was the Associate Director of the Ballistic Research Laboratory at the Aberdeen Proving Grounds in Aberdeen, Maryland where he focused on ballistics research.

While Dederick worked as a mathematician at the Aberdeen Proving Grounds, he was involved with …

A Predictive Model To Predict Cyberattack Using Self-Normalizing Neural Networks, Oluwapelumi Eniodunmo

Theses, Dissertations and Capstones

Cyberattack is a never-ending war that has greatly threatened secured information systems. The development of automated and intelligent systems provides more computing power to hackers to steal information, destroy data or system resources, and has raised global security issues. Statistical and Data mining tools have received continuous research and improvements. These tools have been adopted to create sophisticated intrusion detection systems that help information systems mitigate and defend against cyberattacks. However, the advancement in technology and accessibility of information makes more identifiable elements that can be used to gain unauthorized access to systems and resources. Data mining and classification tools …

Application Of An Organizational Evaluation Capacity Assessment In A Multinational Ngo: A Case Study To Support Applied Practice, Ryan James Smyth

Electronic Theses and Dissertations

As evaluation capacity building (ECB) has rapidly emerged as a practice in human service organizations and as a field of academic inquiry, attention has focused on methods of evaluation capacity building while assessment of organizational evaluation capacity (EC) has lagged behind. To examine the practice of organizational evaluation capacity assessment, this dissertation presents two separate but related studies. In sub-study 1, I present a qualitative evidence synthesis of the research theorizing organizational evaluation capacity models. In sub-study 2, I support the implementation of one of the tools from the evidence-synthesis at a multinational human service organization. I use a concurrent …

Long-Read Sequencing Of The Zebrafish Genome Reorganizes Genomic Architecture, Yelena Chernyavskaya, Xiaofei Zhang, Jinze Liu, Jessica Blackburn

Biostatistics Publications

Background

Nanopore sequencing technology has revolutionized the field of genome biology with its ability to generate extra-long reads that can resolve regions of the genome that were previously inaccessible to short-read sequencing platforms. Over 50% of the zebrafish genome consists of difficult to map, highly repetitive, low complexity elements that pose inherent problems for short-read sequencers and assemblers.

Results

We used long-read nanopore sequencing to generate a de novo assembly of the zebrafish genome and compared our assembly to the current reference genome, GRCz11. The new assembly identified 1697 novel insertions and deletions over one kilobase in length and placed …

Don’T Beep At Me: Using Google Maps Apis To Reduce Driving Anxiety, Daniel Chechelnitsky

Mathematics, Statistics, and Computer Science Honors Projects

Stress while driving is a significant issue that causes automobile incidents. Along with the physical injuries, there is often baggage and trauma associated with these accidents. Wearable health monitoring technology, like Smartwatches, has a real possibility to help people further understand the stress inducing processes of driving. Thus to help with this issue, I propose a Google Maps app extension called: "Don't Beep At Me". This project creates a map that is layered by heart rate instead of speed limit and has great potential to be useful for reducing driving anxiety.

A Participatory Group Process To Collect And Disseminate Covid-19 Needs Assessment Data, Areebah Ahmed

UROP Posters

The Richmond, VA COVID-19 Needs Assessment Survey (RVA CoNA) was created in March 2020 to identify behaviors and needs related to COVID-19 in Richmond area adults ages 18 and over. Results are being used to inform support, strategic efforts, and educational outreach of local community organizations. The purpose of this study is to (1) summarize the process used to develop the RVA CoNA, (2) summarize preliminary survey results from a second phase of data collection as well as initial feedback from community partners, and (3) summarize initial conclusions and results dissemination strategies.Community partners and researchers at Virginia Commonwealth University jointly …

Development And Initial Validation Of An Acculturation Measure For Arab Expatriates In Qatar Using Mixed Methods, Sara Ali Ahmed Zikri

Electronic Theses and Dissertations

Prior research on acculturation has predominantly focused on specific immigrant and ethnic groups in the United States, Europe, and Asia, and there is a lack of publicly available scales that measure acculturation among expatriates in countries of the Gulf Cooperation Council. The purpose of this study was to use a mixed methods research design to develop a theoretical framework of acculturation for white-collar Arab expatriates in Qatar as well as a culturally appropriate self-report acculturation measure. The acculturation stories and experiences of white-collar Arab expatriates in Qatar were qualitatively explored and analyzed, and their findings were used to construct an …

Modeling Digital Camera Monitoring Count Data With Intermittent Zeros For Short-Term Prediction, Eben Afrifa-Yamoah, Ute Mueller

Research outputs 2022 to 2026

Digital camera monitoring has revolutionised survey designs in many fields, as an important source of information. The extended sampling coverage offered by this monitoring scheme makes it preferable compared to other traditional methods of survey. However, data obtained from digital camera monitoring are often highly variable, and characterized by sparse periods of zero counts, interspersed with missing observations due to outages. In practice, missing data of relatively shorter duration are mostly observed and are often imputed using interpolation techniques, ignoring long-term trends leading to inherent estimation biases. In this study, we investigated time series forecasting methods that adequately handle intermittency …

Approximating Bayesian Optimal Sequential Designs Using Gaussian Process Models Indexed On Belief States, Joseph Burris

Theses and Dissertations

Fully sequential optimal Bayesian experimentation can offer greater utility than both traditional Bayesian designs and greedy sequential methods, but practically cannot be solved due to numerical complexity and continuous outcome spaces. Approximate solutions can be found via approximate dynamic programming, but rely on surrogate models of the expected utility at each trial of the experiment with hand-chosen features or use methods which ignore the underlying geometry of the space of probability distributions. We propose the use of Gaussian process models indexed on the belief states visited in experimentation to provide utility-agnostic surrogate models for approximating Bayesian optimal sequential designs which …

Informative G-Prior For Linear Models, Yu-Fang Chien

Graduate Research Theses & Dissertations

Zellner's objective g-prior has been widely used in linear regression models due to its simple interpretation and computational tractability in evaluating marginal likelihoods. However, the g-prior further allows portioning the prior variability explained by the linear predictor versus that of pure noise. Here, a novel, yet remarkably simple g-prior speci_cation is proposed when a subject-matter expert has information on the marginal distribution of the response yi. The approach is extended for use in mixed models with some surprising, but intuitive results. Also, this formulation of g-prior is compared with other approaches via simulation studies.

Using Deep Neural Networks To Analyze Precision Agriculture Data, Stephanie Liebl

Electronic Theses and Dissertations

As the population of the Earth increases, there is a growing need for food to feed the inhabitants. Precision agriculture offers techniques and tools that can be used to help accommodate the growing population. One specific precision agriculture tool is remote sensing data, which can be used to image fields as an effort to better predict or understand the crops. In this thesis, deep neural networks are used to evaluate various spatial, spectral, and temporal resolutions of three different satellite images to determine which best predicts corn yield. The main metrics we used to evaluate the models were R-squared (R2), …

Sampling Distribution Of Non-Overlap Indices Using Bootstrapping Procedure : A Monte Carlo Simulation Study And Empirical Demonstration, Xinyun Xu

Legacy Theses & Dissertations (2009 - 2024)

Statistics can be either parametric or non-parametric, depending on whether distributional assumptions about the data and sampling distributions are required. Parametric and non-parametric approaches each include a variety of inferential methods. These methods can be seen in the field of single-case experimental design (SCED). By reviewing one of the most used groups of statistics for SCED research (Jamshidi et al., 2022; Maggin et al., 2011), the non-overlap indices, one major issue arose. It is challenging to make inferences and interpretations about non-overlap indices. The main reason for this issue is that non-overlap indices have inconsistent and unknown sampling distributions (under …

The Role Of Health Expenditure On Health Outcomes: Evidence In West Africa Countries., Festus Efosa Eriamiatoe

Graduate Research Theses & Dissertations

This study investigates the role of health expenditure on health outcomes in West Africa countries. Using the Grossman theoretical framework, other variables that affect health outcomes were also examined. Sixteen countries of West Africa with yearly data spanning between the period of 19 years (2000-2019) was used in this study. The health outcomes examined include life expectancy and neonatal and under-5 mortality rates. The regressors used in the study include domestic government health expenditure per capita, domestic private health expenditure per capita, external health expenditure per capita, carbon-dioxide emission metric ton per capita, human immunodeficiency virus (HIV), unemployment, GDP per …

A Simple And Robust Alternative To Bland-Altman Method Of Assessing Clinical Agreement, Abhaya Indrayan Prof

COBRA Preprint Series

Clinical agreement between two quantitative measurements on a group of subjects is generally assessed with the help of the Bland-Altman (B-A) limits. These limits only describe the dispersion of disagreements in 95% cases and do not measure the degree of agreement. The interpretation regarding the presence or absence of agreement by this method is based on whether B-A limits are within the pre-specified externally determined clinical tolerance limits. Thus, clinical tolerance limits are necessary for this method. We argue in this communication that the direct use of clinical tolerance limits for assessing agreement without the B-A limits is more effective …

Using Short Bursts To Optimize Redistricting In Georgia, Vedika Vishweshwar

CMC Senior Theses

Identifying extreme outliers in large state spaces is a difficult prob-
lem. I consider this problem in the context of finding political district-
ing plans that maximize the number of districts in which the majority
of the population is from a minority group, such as African Americans.
Since the set of all possible districting plans is enormous and unfeasi-
ble to examine in practice, this paper proposes a sampling method to
find these outlying plans. Specifically, this paper experiments with short
bursts in the context of minority voting rights in Georgia. Short bursts
are a type of Markov Chain in …