Applied Mathematics Commons^™

Comparison Of Fecal Microbiota In Children With Autism Spectrum Disorders And Neurotypical Siblings In The Simons Simplex Collection, Joshua S. Son, Ling J. Zheng, Leahana M. Rowehl, Ellen Li, Xinyu Tian, Yuanhao Zhang, Wei Zhu, Leighann Litcher-Kelly, Kenneth D. Gadow, Grace Gathungu, Charles E. Robertson, Diana Ir, Daniel N. Frank

Department of Applied Mathematics & Statistics Faculty Publications

In order to assess potential associations between autism spectrum disorder (ASD) phenotype, functional GI disorders and fecal microbiota, we recruited simplex families, which had only a single ASD proband and neurotypical (NT) siblings, through the Simons Simplex Community at the Interactive Autism Network (SSC@IAN). Fecal samples and metadata related to functional GI disorders and diet were collected from ASD probands and NT siblings of ASD probands (age 7–14). Functional gastrointestinal disorders (FGID) were assessed using the parent-completed ROME III questionnaire for pediatric FGIDs, and problem behaviors were assessed using the Child Behavior Check List (CBCL). Targeted quantitative polymerase chain reaction …

A Machine Learning Approach To Post-Market Surveillance Of Medical Devices, Jonathan Bates, Shu-Xia Li, Craig Parzynski, Ronald Coifman, Harlan Krumholz, Joseph Ross

Yale Day of Data

Post-market surveillance is a collection of processes and activities used by product manufacturers and regulators, such as the U.S. Food and Drug Administration (FDA) to monitor the safety and effectiveness of medical devices once they are available for use “on the market”. These activities are designed to generate information to identify poorly performing devices and other safety problems, accurately characterize real-world device performance and clinical outcomes, and facilitate the development of new devices, or new uses for existing devices. Typically, a device is monitored by comparing adverse events in the exposed population to a matched unexposed population. This research considers …

A Hierarchical Graph For Nucleotide Binding Domain 2, Samuel Kakraba

Electronic Theses and Dissertations

One of the most prevalent inherited diseases is cystic fibrosis. This disease is caused by a mutation in a membrane protein, the cystic fibrosis transmembrane conductance regulator (CFTR). CFTR is known to function as a chloride channel that regulates the viscosity of mucus that lines the ducts of a number of organs. Generally, most of the prevalent mutations of CFTR are located in one of two nucleotide binding domains, namely, the nucleotide binding domain 1 (NBD1). However, some mutations in nucleotide binding domain 2 (NBD2) can equally cause cystic fibrosis. In this work, a hierarchical graph is built for NBD2. …

The Relationship Among Math Anxiety, Mathematical Performance, And Math Education In Undergraduate Nursing Students, Joshua D. Beall, Troy Roebuck, Paul Penkalsky

Williams Honors College, Honors Research Projects

Although nurses spend up to 40% of their day calculating and administering medication doses, undergraduate nursing students often perform poorly on nursing math exams. The purpose of this study was (a) to examine the relationship among mathematical education, performance, and anxiety and (b) to compare the mathematical education, performance, and anxiety in sophomore and senior baccalaureate nursing students at a public university in the Midwest. This cross-sectional, descriptive study was guided by Bandura's self-efficacy theory. Math performance was measured with an 11-item math instrument, math education was measured with number of math courses, and math anxiety was measured with Fennema–Sherman …

Quantitative Modeling Of Spatiotemporal Systems: Simulation Of Biological Systems And Analysis Of Error Metric Effects On Model Fitting, James Hengenius

Open Access Dissertations

Understanding the biophysical processes underlying biological and biotechnological processes is a prerequisite for therapeutic treatments and technological innovation. With the exponential growth of computational processing speed, experimental findings in these fields have been complemented by dynamic simulations of developmental signaling and genetic interactions. Models provide means to evaluate "emergent" properties of systems sometimes inaccessible by reductionist approaches, making them test beds for biological inference and technological refinement.^ The complexity and interconnectedness of biological processes pose special challenges to modelers; biological models typically possess a large number of unknown parameters relative to their counterparts in other physical sciences. Estimating these parameter …

Structured Deterministic Models Applied To Malaria And Other Endemic Diseases, Katia Patricia Vogt Geisse

Open Access Dissertations

This thesis includes modeling studies on three structured deterministic models. These models are used to study the disease dynamics of malaria or the joint disease dynamics of HIV and HSV-2. Each of the models includes multiple components containing individuals in various epidemiological classes for the purpose of addressing questions that are of interests to biologists and epidemiologists. Some of the compartments have a continuous age-structure, which is necessary for studying the specific biological questions under investigation.^ In Chapter 2 a chronological-age structured deterministic model for malaria is presented. The model includes the human and mosquito populations with the human population …

A Comparison Of Five Malaria Transmission Models: Benchmark Tests And Implications For Disease Control, Dorothy I. Wallace, Ben S. Southworth, Xun Shi, Jonathan W. Chipman, Andrew K. Githeko

Dartmouth Scholarship

Background: Models for malaria transmission are usually compared based on the quantities tracked, the form taken by each term in the equations, and the qualitative properties of the systems at equilibrium. Here five models are compared in detail in order to develop a set of performance measures that further illuminate the differences among models.

Methods: Five models of malaria transmission are compared. Parameters are adjusted to correspond to similar biological quantities across models. Nine choices of parameter sets/initial conditions are tested for all five models. The relationship between malaria incidence in humans and (1) malaria incidence in vectors, (2) man-biting …

A Likelihood Approach To Estimate The Number Of Co-Infections, Kristian A. Schneider, Ananias A. Escalante

Harold W. Manter Laboratory of Parasitology: Library Materials

Article abstract:

The number of co-infections of a pathogen (multiplicity of infection or MOI) is a relevant parameter in epidemiology as it relates to transmission intensity. Notably, such quantities can be built into a metric in the context of disease control and prevention. Having applications to malaria in mind, we develop here a maximum-likelihood (ML) framework to estimate the quantities of interest at low computational and no additional costs to study designs or data collection. We show how the ML estimate for the quantities of interest and corresponding confidence-regions are obtained from multiple genetic loci. Assuming specifically that infections are …

Physiologically-Based Pharmacokinetic Model For Ertapenem, Whitney Forbes

Electronic Theses and Dissertations

Ertapenem is a carbapenem used to treat a wide range of bacterial infections. What sets ertapenem apart from other carbapenems is its longer half-life which implies it need only be administered once daily. We developed a physiologically-based pharmacokinetic model for the distribution of ertapenem within the body. In the model, parameters such as human body weight and height, age, organ volumes, blood flow rates, and partition coefficients of particular tissues are used to examine the absorption, distribution, metabolism, and excretion of ertapenem. The total and free blood concentrations found were then compared to experimental data. We then examined the sensitivity …

A Comparison Of Clustering And Missing Data Methods For Health Sciences, Ran Zhao, Deanna Needell, Christopher Johansen, Jerry L. Grenard

CMC Faculty Publications and Research

In this paper, we compare and analyze clustering methods with missing data in health behavior research. In particular, we propose and analyze the use of compressive sensing's matrix completion along with spectral clustering to cluster health related data. The empirical tests and real data results show that these methods can outperform standard methods like LPA and FIML, in terms of lower misclassification rates in clustering and better matrix completion performance in missing data problems. According to our examination, a possible explanation of these improvements is that spectral clustering takes advantage of high data dimension and compressive sensing methods utilize the …

Numerical Algorithms For Solving A Generalized Cancer Chemotherapy Problem, Frank Nani, Mingxian Jin

Math and Computer Science Faculty Working Papers

In this paper, two elaborate numerical algorithms are presented for solving the Nani- Oguztoreli functional differential equations associated with cell-cycle specific cancer chemotherapy. The generalized cell-cycle specific cancer chemotherapy model of Nani- Oguztoreli contains discrete time delays which represent the times that the cancer cells spend in each cell-cycle phase. The model also takes into account that inter-cell cycle phase transition rate constants, recruitment of resting cells from the GO phase, and effect of chemotherapy drug on cells in each phase. The algorithms utilize a modified version of the Method of Steps algorithms. The constructed numerical schemes can be implemented …

An Epidemic Model Structured By The Time Since Last Infection, Jorge Alturo Alfaro Murillo

Open Access Dissertations

Epidemiological models structured by time since infection have their origin in the seminal work of 1927 by Kermack and McKendrick. Compared to ordinary differential equations (ODE) models, they are able to capture differences in infectivity of the individuals in a more suitable manner. Their use declined in the second half of the 20th century, probably because the theory for ODE models is more robust, complete and has proved successful in providing insights and predictions for many epidemiological problems. Nevertheless, it is important to understand in what occasions the inclusion of time since infection may alter the outcomes in a significant …

Juxtaposing Nasa’S Aeronet Aod With Carb Pm Data Over The San Joaquin Valley To Facilitate Multi-Angle Imaging Spectroradiometer (Misr) Pm Pollution Research, John Kanemoto

STAR Program Research Presentations

Airborne particulate matter (PM) has been shown to increase the risk for asthma, chronic bronchitis, cardiopulmonary complications, and respiratory cell membrane damage/infection/leakage. PM levels are currently analyzed from two perspectives: stationary land-based monitoring (LBM) sites and total Aerosol Optical Depth (AOD) atmospheric column measurements. Both perspectives often leave miles of space between measuring locations and will have a continually increasing cost from introducing/maintaining sites. The Multi-angle Imaging SpectroRadiometer (MISR) satellite team hopes to begin investigating/archiving PM levels comprehensively via inputting MISR AOD measurements into a function/model which predicts the amount of ground level PM.

In the future, multivariable spatial correlations …

Effect Of Variable Dose Rate On Biologically Effective Dose, Vadim Y. Kuperman, Gregory S. Spradlin

Publications

Purpose: to investigate the effect of variable dose rate on biologically effective dose ( BED ).

Materials and methods: by using the linear-quadratic (LQ) model with bi-exponential repair, we analytically determine the time-dependent dose rate R ~ which minimizes the effective protraction factor ( eff G ) and BEDunder the condition of fixed fraction time and dose per fraction.  Because normal tissue complication probability ( NTCP) monotonically decreases with decreasingBED , the dose rate R ~ also minimizes NTCP.

Results: the dependences of Geff, BED, and NTCP on fraction time were determined for different radiobiological parameters and two different …

Substance Abuse Via Legally Prescribed Drugs: The Case Of Vicodin In The United States, Wendy K. Caldwell, Benjamin Freedman, Luke Settles, Michael M. Thomas, Anarina Murillo, Erika Camacho, Stephen Wirkus

Faculty Articles

Vicodin is the most commonly prescribed pain reliever in the United States. Research indicates that there are two million people who are currently abusing Vicodin, and the majority of those who abuse Vicodin were initially exposed to it via prescription. Our goal is to determine the most effective strategies for reducing the overall population of Vicodin abusers. More specifically, we focus on whether prevention methods aimed at educating doctors and patients on the potential for drug abuse or treatment methods implemented after a person abuses Vicodin will have a greater overall impact. We consider one linear and two non-linear compartmental …

Functional Data Analysis To Guide A Conditional Likelihood Regression In A Case-Crossover Study Investigating Whether Social Characteristics Modify The Health Effects Of Air Pollution, Juana Maribel Herrera Hernandez

Open Access Theses & Dissertations

In this study we are focused on exploring whether social characteristics modify the relationship between air pollution and hospitalizations due to asthma or chronic pulmonary obstructive disease (COPD) in El Paso, Tx. The case-crossover design with conditional regression analysis was used, here the controls and the case are the same subject at different

times and has the advantage of removing confounding by permanently confounding factors. Social characteristics are included in the models as interactions with the pollutants, variables included are age, sex, ethnicity and insurance status as indicator for the socio-economic status. The pollutant's lags were chosen using the historical …

Hydrodynamic Modeling Of Ns-Laser Ablation, David Autrique, Vasilios Alexiades, Harihar Khanal

Publications

Laser ablation is a versatile and widespread technique, applied in an increasing number of medical, industrial and analytical applications. A hydrodynamic multiphase model describing nanosecond-laser ablation (ns- LA) is outlined. The model accounts for target heating and mass removal mechanisms as well as plume expansion and plasma formation. A copper target is placed in an ambient environment consisting of helium and irradiated by a nanosecond-laser pulse. The effect of variable laser settings on the ablation process is explored in 1-D numerical simulations.

Time-Stepping For Laser Ablation, Harihar Khanal, David Autrique, Vasilios Alexiades

Publications

Nanosecond laser ablation is a popular technique, applied in many areas of science and technology such as medicine, archaeology, chemistry, environmental and materials sciences. We outline a computational model for radiative and collisional processes occurring during ns-laser ablation, and compare the performance of various low and high order time-stepping algorithms.

Multiple Subject Barycentric Discriminant Analysis (Musubada): How To Assign Scans To Categories Without Using Spatial Normalization, Hervé Abdi, Lynne J. Williams, Andrew C. Connolly, M. Ida Gobbini

Dartmouth Scholarship

We present a new discriminant analysis (DA) method called Multiple Subject Barycentric Discriminant Analysis (MUSUBADA) suited for analyzing fMRI data because it handles datasets with multiple participants that each provides different number of variables (i.e., voxels) that are themselves grouped into regions of interest (ROIs). Like DA, MUSUBADA (1) assigns observations to predefined categories, (2) gives factorial maps displaying observations and categories, and (3) optimally assigns observations to categories. MUSUBADA handles cases with more variables than observations and can project portions of the data table (e.g., subtables, which can represent participants or ROIs) on the factorial maps. Therefore MUSUBADA can …

A Mathematical Model For Dengue Fever In A Virgin Environment, Jason K. Bowman

Senior Honors Projects

Dengue is a mosquito-borne viral infection found in tropical and subtropical regions around the world. The disease was named in 1779 and the first recorded epidemic of it occurred simultaneously on three continents within the following decade. Dengue is characterized by flu-like symptoms and, while its symptoms are generally reported as quite unpleasant, is rarely fatal. However, in some cases patients can contract a more serious form of the disease, known as Dengue Hemorrhagic Fever, which is far more dangerous. The World Health Organization estimates that today over 2.5 billion people are at risk for Dengue (over 40% of the …

Border Hispanics’ Physical Activity Improvement In A Chronic Disease Prevention Program, Lu Xu

Theses and Dissertations - UTB/UTPA

In seeking of effective prevention programs to improve physical activities, we want to examine the factors related to physical activities improvement in Alliance for a Healthy Border, a chronic disease prevention program with pre-post-post evaluations through 12 federally qualified community health centers serving primarily Hispanics in communities along the U.S.- Mexico border. Logistic regression was performed to examine the association between physical activity and twenty predictors at baseline. Multinomial regression was used to examine the determinants of physical activities improvement at two time points: program end and post six-months. Socio-demographic, baseline health condition factors, and determination of doing physical activity …

The Radon Transform And The Mathematics Of Medical Imaging, Jen Beatty

Honors Theses

Tomography is the mathematical process of imaging an object via a set of finite slices. In medical imaging, these slices are defined by multiple parallel X-ray beams shot through the object at varying angles. The initial and final intensity of each beam is recorded, and the original image is recreated using this data for multiple slices. I will discuss the central role of the Radon transform and its inversion formula in this recovery process.

Constrained Optimal Control For A Multi-Group Discrete Time Influenza Model, Paula Andrea Gonzalez Parra

Open Access Theses & Dissertations

During the last decades, mathematical epidemiological models have been used to understand the dynamics of infectious diseases and guide public health policy. In particular, several continuous models have been considered to study single in uenza outbreaks and the impact of dierent control policies. In this dissertation, a discrete time model is introduced in order to study optimal control strategies for in uenza transmission; since epidemiological data is collected on discrete units of time, a discrete formulation is more ecient. From a mathematical point of view, continuous time model are easier to analyze, however, the numerical solution of discrete-time models is …

Flexible Distributed Lag Models Using Random Functions With Application To Estimating Mortality Displacement From Heat-Related Deaths, Roger D. Peng

Johns Hopkins University, Dept. of Biostatistics Working Papers

No abstract provided.

Modelling Β2ar Regulation, Sharat J. Vayttaden

Dissertations and Theses (Open Access)

The β2 adrenergic receptor (β2AR) regulates smooth muscle relaxation in the vasculature and airways. Long- and Short-acting β-agonists (LABAs/SABAs) are widely used in treatment of chronic obstructive pulmonary disorder (COPD) and asthma. Despite their widespread clinical use we do not understand well the dominant β2AR regulatory pathways that are stimulated during therapy and bring about tachyphylaxis, which is the loss of drug effects. Thus, an understanding of how the β2AR responds to various β-agonists is crucial to their rational use. Towards that end we have developed deterministic models that explore the mechanism of drug- induced β2AR regulation. These mathematical models …

Use Of Optimal Control Models To Predict Treatment Time For Managing Tick-Borne Disease, Holly D. Gaff, Elsa Schaefer, Suzanne Lenhart

Biological Sciences Faculty Publications

Tick-borne diseases have been on the rise recently, and correspondingly, there is an increased interest in implementing control measures to decrease the risk. Optimal control provides an ideal tool to identify the best method for reducing risk while accounting for the associated costs. Using a previously published model, a variety of frameworks are assessed to identify the key factors influencing mitigation strategies. The level and duration of tick-reducing efforts are key metrics for understanding the successful reduction in tick-borne disease incidence. The results show that the punctuated nature of the tick's life history plays a critical role in reducing risk …

A Comparison Of Spatio-Temporal Prediction Methods Of Cancer Incidence In The U.S, Michelle Hamlyn

UNLV Theses, Dissertations, Professional Papers, and Capstones

Cancer is the cause of one out of four deaths in the United States, and in 2009, researchers expected over 1.5 million new patients to be diagnosed with some form of cancer. People diagnosed with cancer, whether a common or rare type, need to undergo treatments, the amount and kind of which will depend on the severity of the cancer. So how do healthcare providers know how much funding is needed for treatment? What would better enable a pharmaceutical company to determine how much to allocate for research and development of drugs, the amount of each drug to manufacture, or …

Variable Importance Analysis With The Multipim R Package, Stephan J. Ritter, Nicholas P. Jewell, Alan E. Hubbard

U.C. Berkeley Division of Biostatistics Working Paper Series

We describe the R package multiPIM, including statistical background, functionality and user options. The package is for variable importance analysis, and is meant primarily for analyzing data from exploratory epidemiological studies, though it could certainly be applied in other areas as well. The approach taken to variable importance comes from the causal inference field, and is different from approaches taken in other R packages. By default, multiPIM uses a double robust targeted maximum likelihood estimator (TMLE) of a parameter akin to the attributable risk. Several regression methods/machine learning algorithms are available for estimating the nuisance parameters of the models, including …

Noise, Delays, And Resonance In A Neural Network, Austin Quan

HMC Senior Theses

A stochastic-delay differential equation (SDDE) model of a small neural network with recurrent inhibition is presented and analyzed. The model exhibits unexpected transient behavior: oscillations that occur at the boundary of the basins of attraction when the system is bistable. These are known as delay-induced transitory oscillations (DITOs). This behavior is analyzed in the context of stochastic resonance, an unintuitive, though widely researched phenomenon in physical bistable systems where noise can play in constructive role in strengthening an input signal. A method for modeling the dynamics using a probabilistic three-state model is proposed, and supported with numerical evidence. The potential …

An Extensible Mathematical Model Of Glucose Metabolism, Caleb L. Adams

Mathematics & Statistics Theses & Dissertations

The American Diabetes Association reports that diabetes is the fifth leading cause of death by disease in the United States. An estimated 23.6 million individuals, or seven percent of the population, have diabetes. Nearly one-third are unaware that they have the disease. The total of the direct and indirect medical costs associated with diabetes in 2007 was projected to be $174 billion, or approximately one out of every ten health care dollars.

One must understand the glucose regulatory system of the healthy body to understand diabetes. Blood glucose concentration returns to a constant level after eating and is maintained during …