Statistics and Probability Commons^™

Age-Dependent Ventilator-Induced Lung Injury, Quintessa Hay, Christopher Grubb, Rebecca L. Heise, Sarah Minucci, Michael S. Valentine, Jennifer Van Mullekom, Angela M. Reynolds

Biology and Medicine Through Mathematics Conference

No abstract provided.

Principal Response Curve Analysis Of Arthropod Community Abundance Data With Sparse Subsets, Changjian Jiang, C. R. Brown, P. Asiimwe, Chen Meng, Adam W. Schapaugh

Conference on Applied Statistics in Agriculture and Natural Resources

Principal response curve (PRC) analysis was applied to an assessment of the ecological impact of the genetically-modified (GM), insect-resistant, cotton MON 88702 on predatory Hemiptera communities in the field. The field community was represented by ten taxa collected ten times across the season at six sites, in which individual taxa were not observed in at least 25% of the time (unique site x collection combinations). These complete absences and those nearly so, called sparse subsets of the data in this investigation, were the result of geoclimatic and seasonal variations, which are both independent of the treatment effect for which the …

Handling Non-Detects With Imputation In A Nested Design: A Simulation Study, Rose Adjei, John R. Stevens

Conference on Applied Statistics in Agriculture and Natural Resources

In this paper, a simulation study was conducted to assess whether it is ideal to address the issue of non-detects in data using a traditional substitution approach for non-detects, imputation, or a non-imputation based approach. Simulated data used were simple nested designs motivated by a real-life data in a study of bumble bee activity in a commercial cherry orchard by Kuivila et al. (2021). The simulated data were generated at different thresholds or censoring levels and at different effect sizes. For each simulated data, seven popular existing techniques to handle non-detects were applied: (i) Zero substitution, (ii) Substitution with half …

Overview Of Optimal Experimental Design And A Survey Of Its Expanse In Application To Agricultural Studies, Stephen J. Walsh

Conference on Applied Statistics in Agriculture and Natural Resources

Optimal Design of Experiments is currently recognized as the modern dominant approach to planning experiments in industrial engineering and manufacturing applications. This approach to design has gained traction among practitioners in the last two decades on two-fronts: 1) optimal designs are the result of a complicated optimization calculation and recent advances in both computing efficiency and algorithms have enabled this approach in real time for practitioners, and 2) such designs are now popular because they allow the researcher to ‘design for the experiment’ by working constraints, cost, number of experiments, and the model of the intended post-hoc data analysis into …

An Econometric Analysis Of Collegiate Player Performance To Create A Model For Forecasting Contributions To Team Success, Evan Seely

Undergraduate Theses

At the conclusion of each basketball season, each conference selects 1^st, 2^nd, and sometimes 3^rd all-conference teams based on player performance for that season. Often, these all-conference teams reflect biases in the media rather than evaluations based on player performance alone. The baseball statistic Wins Above Replacement, WAR, is useful in quantifying the impact of each player through the number of wins contributed to his respective team by comparing each player to a designated replacement level player. This statistic can also be applied to basketball analysis to perform a similar function as in baseball, despite …

Comparing Artificial-Intelligence Techniques With State-Of-The-Art Parametric Prediction Models For Predicting Soybean Traits, Susweta Ray, Diego Jarquin, Reka Howard

Department of Statistics: Faculty Publications

Soybean [Glycine max (L.) Merr.] is a significant source of protein and oil and is also widely used as animal feed. Thus, developing lines that are superior in terms of yield, protein, and oil content is important to feed the ever-growing population. As opposed to high-cost phenotyping, genotyping is both cost and time efficient for breeders because evaluating new lines in different environments (location–year combinations) can be costly. Several genomic prediction (GP) methods have been developed to use the marker and environment data effectively to predict the yield or other relevant phenotypic traits of crops. Our study compares a conventional …

Contribution To Data Science: Time Series, Uncertainty Quantification And Applications, Dhrubajyoti Ghosh

Arts & Sciences Graduate Student Theses and Dissertations

Time series analysis is an essential tool in modern world statistical analysis, with a myriad of real data problems having temporal components that need to be studied to gain a better understanding of the temporal dependence structure in the data. For example, in the stock market, it is of significant importance to identify the ups and downs of the stock prices, for which time series analysis is crucial. Most of the existing literature on time series deals with linear time series, or with Gaussianity assumption. However, there are multiple instances where the time series shows nonlinear trends, or when the …

Statistical Analyses Of Hemp Cannabinoid Test Results, Rachel J. Stegmeier

Senior Honors Projects, 2020-current

Cannabis sativa L. is a flowering plant used for recreational and industrial purposes that produces a class of compounds called cannabinoids. Industrial hemp is a strain of Cannabis sativa L. that has been propagated to have a low Δ 9 tetrahydrocannabinol (Δ⁹THC) and a high cannabidiol (CBD) content. With recent advancements in legislation, farms are now growing hemp for fiber, CBD production and other hemp derived product purposes but crops risk being destroyed if THC content levels exceed the current maximum legal limit of 0.3%. For the present study hemp samples were dried, ground, extracted with various alcohols, …

Needs Assessment Of Southeastern United States Vector Control Agencies: Capacity Improvement Is Greatly Needed To Prevent The Next Vector-Borne Disease Outbreak, Kyndall C. Dye-Braumuller, Jennifer R. Gordon, Danielle John, Josie Morrissey, Kaci Mccoy, Rhoel R. Dinglasan, Melissa Nolan Ph.D., Mph

Faculty Publications

A national 2017 vector control capacity survey was conducted to assess the United States’ (U.S.’s) ability to prevent emerging vector-borne disease. Since that survey, the southeastern U.S. has experienced continued autochthonous exotic vector-borne disease transmission and establishment of invasive vector species. To understand the current gaps in control programs and establish a baseline to evaluate future vector control efforts for this vulnerable region, a focused needs assessment survey was conducted in early 2020. The southeastern U.S. region was targeted, as this region has a high probability of novel vector-borne disease introduction. Paper copies delivered in handwritten envelopes and electronic copies …

Impact Of Climate Oscillations/Indices On Hydrological Variables In The Mississippi River Valley Alluvial Aquifer., Meena Raju

Theses and Dissertations

The Mississippi River Valley Alluvial Aquifer (MRVAA) is one of the most productive agricultural regions in the United States. The main objectives of this research are to identify long term trends and change points in hydrological variables (streamflow and rainfall), to assess the relationship between hydrological variables, and to evaluate the influence of global climate indices on hydrological variables. Non-parametric tests, MMK and Pettitt’s tests were used to analyze trend and change points. PCC and Streamflow elasticity analysis were used to analyze the relationship between streamflow and rainfall and the sensitivity of streamflow to rainfall changes. PCC and MLR analysis …

Evaluating Soil Health Changes Following Cover Crop And No-Till Integration Into A Soybean (Glycine Max) Cropping System In The Mississippi Alluvial Valley, Alexandra Gwin Firth

Theses and Dissertations

The transition of natural landscapes to intensive agricultural uses has resulted in severe loss of soil organic carbon (SOC), increased CO₂ emissions, river depletion, and groundwater overdraft. Despite negative documented effects of agricultural land use (i.e., soil erosion, nutrient runoff) on critical natural resources (i.e., water, soil), food production must increase to meet the demands of a rising human population. Given the environmental and agricultural productivity concerns of intensely managed soils, it is critical to implement conservation practices that mitigate the negative effects of crop production and enhance environmental integrity. In the Mississippi Alluvial Valley (MAV) region of Mississippi, USA, …

A Two-Layer Model Explains Higher-Order Feature Selectivity Of V2 Neurons, Timothy D. Oleskiw, Justin D. Lieber, J. Anthony Movshon, Eero P. Simoncelli

MODVIS Workshop

Neurons in cortical area V2 respond selectively to higher-order visual features, such as the quasi-periodic structure of natural texture. However, a functional account of how V2 neurons build selectivity for complex natural image features from their inputs – V1 neurons locally tuned for orientation and spatial frequency – remains elusive.

We made single-unit recordings in area V2 in two fixating rhesus macaques. We presented stimuli composed of multiple superimposed grating patches that localize contrast energy in space, orientation, and scale. V2 activity is modeled via a two-layer linear-nonlinear network, optimized to use a sparse combination of V1-like outputs to account …

Shining A Light On Marginal Food Insecurity In An Understudied Population Comment, Angela D. Liese

Faculty Publications

No abstract provided.

Novel Instance-Level Weighted Loss Function For Imbalanced Learning, Trent Geisler

Doctor of Data Science and Analytics Dissertations

Binary classification using imbalanced datasets remains a challenge. Typically, supervised learning algorithms minimize the binary cross-entropy objective function to determine the final parameter estimates. This objective function assumes an equal class distribution between the minority (i.e. events) and majority (i.e. non-events) classes, which almost never exists in real-world modeling. In the imbalanced data setting, the equal class distribution is grossly violated, and the resulting parameter estimates are biased toward the majority class. To overcome the bias and improve model generalization, we focus on modifying the original binary cross-entropy objective function by uniquely weighting each minority class observation. We base our …

Increasing Perceived Realism Of Objects In A Mixed Reality Environment Using 'Diminished Virtual Reality', Logan Scott Parker

Honors Theses

With the recent explosion of popularity of virtual and mixed reality, an important question has arisen: “Is there a way to create a better blend of real and virtual worlds in a mixed reality experience?” This research attempts to determine whether a visual filter can be created and applied to virtual objects to better convince the brain into interpreting a composite of virtual and real views as one seamless view. The method devised in this thesis is being called 'Diminished Virtual Reality'. The results found in this study show that when presented with a scene composed of a combination of …

The Critical Value Of Maternal And Child Health (Mch) To Graduate Training In Public Health: A Framework To Guide Education, Research And Practice Comment, Julianna Deardorff, Michelle Menser Tissue, Patricia Elliott, Arden Handler, Cheryl Vamos, Zobeida Bonilla, Renee Turchi, Cecilia Sem Obeng, Jihong Liu, Holly Grason

Faculty Publications

Introduction

In light of persistent health inequities, this commentary describes the critical role of maternal and child health (MCH) graduate training in schools and programs of public health (SPPH) and illustrates linkages between key components of MCH pedagogy and practice to 2021 CEPH competencies.

Methods

In 2018, a small working group of faculty from the HRSA/MCHB-funded Centers of Excellence (COEs) was convened to define the unique contributions of MCH to SPPH and to develop a framework using an iterative and consensus-driven process. The working group met 5 times and feedback was integrated from the broader faculty across the 13 COEs. …

Factors Affecting Time To Recovery: A Covid-19 Survival Analysis, Fernanda Montoya

Honors Capstones

This project is focused on the recovery rates of patients diagnosed with COVID-19 after different clinical trial drug treatments. Data for the clinical trial studied was obtained from the National Institute of Allergy and Infectious Diseases for the primary purpose of a survival analysis on patient time to recovery under a placebo and therapeutic drug treatment. Specifically, patients in this clinical trial were randomly selected to receive remdesivir, an antiviral drug, in combination with a placebo or baricitinib, a janus kinase inhibitor drug. Cox PH models were used to identify how the different treatment drugs affect time to recovery and …

Comparative Transcriptomic Study Between Cyanobacteria That Contain Chlorophyll D And Those That Lack Chlorophyll D, Fernanda Montoya

Honors Capstones

All cyanobacteria, which perform oxygenic photosynthesis on Earth, contain the photosynthetic pigment chlorophyll a (Chl a) that absorbs light in the violet and red region of the visible spectrum. Cyanobacteria of the Acaryochloris species, however, contain the rare photosynthetic pigment chlorophyll d (Chl d) that absorbs light in the far-red region. Chl d’s ability to absorb light in this region allows it to avoid competing with other photosynthetic organisms for light. Creating a photosystem that uses Chl d in plants would be of great use for agricultural land optimization, but requires knowledge of the biosynthetic pathways of …

Dietary Score Associations With Markers Of Chronic Low-Grade Inflammation: A Cross-Sectional Comparative Analysis Of A Middle- To Older-Aged Population, Seán R. Miller, Pilar Navarro, Janas M. Harrington, Nitin Shivappa Mbbs, Mph, Ph.D., James Hébert Scd, Ivan J. Perry, Catherine M. Phillips

Faculty Publications

Purpose

To assess relationships between the Dietary Approaches to Stop Hypertension (DASH), Mediterranean Diet (MD), Dietary Inflammatory Index (DII^®) and Energy-adjusted DII (E-DII™) scores and pro-inflammatory cytokines, adipocytokines, acute-phase response proteins, coagulation factors and white blood cells.

Methods

This was a cross-sectional study of 1862 men and women aged 46–73 years, randomly selected from a large primary care centre in Ireland. DASH, MD, DII and E-DII scores were derived from validated food frequency questionnaires. Correlation and multivariate-adjusted linear regression analyses with correction for multiple testing were performed to examine dietary score relationships with biomarker concentrations.

Results

In fully …

Generating A Dataset For Comparing Linear Vs. Non-Linear Prediction Methods In Education Research, Jack Mauro, Elena Martinez, Anna Bargagliotti

Honors Thesis

Machine learning is often used to build predictive models by extracting patterns from large data sets. Such techniques are increasingly being utilized to predict outcomes in the social sciences. One such application is predicting student success. Machine learning can be applied to predicting student acceptance and success in academia. Using these tools for education-related data analysis, may enable the evaluation of programs, resources and curriculum. Currently, research is needed to examine application, admissions, and retention data in order to address equity in college computer science programs. However, most student-level data sets contain sensitive data that cannot be made public. To …