Second-Order, Fully Decoupled, Linearized, And Unconditionally Stable Scalar Auxiliary Variable Schemes For Cahn–Hilliard–Darcy System,
2022
Missouri University of Science and Technology
Second-Order, Fully Decoupled, Linearized, And Unconditionally Stable Scalar Auxiliary Variable Schemes For Cahn–Hilliard–Darcy System, Yali Gao, Xiaoming He, Yufeng Nie
Mathematics and Statistics Faculty Research & Creative Works
In this paper, we establish the fully decoupled numerical methods by utilizing scalar auxiliary variable approach for solving Cahn–Hilliard–Darcy system. We exploit the operator splitting technique to decouple the coupled system and Galerkin finite element method in space to construct the fully discrete formulation. The developed numerical methods have the features of second order accuracy, totally decoupling, linearization, and unconditional energy stability. The unconditionally stability of the two proposed decoupled numerical schemes are rigorously proved. Abundant numerical results are reported to verify the accuracy and effectiveness of proposed numerical methods.
Conservative Unconditionally Stable Decoupled Numerical Schemes For The Cahn–Hilliard–Navier–Stokes–Darcy–Boussinesq System,
2022
Missouri University of Science and Technology
Conservative Unconditionally Stable Decoupled Numerical Schemes For The Cahn–Hilliard–Navier–Stokes–Darcy–Boussinesq System, Wenbin Chen, Daozhi Han, Xiaoming Wang, Yichao Zhang
Mathematics and Statistics Faculty Research & Creative Works
We propose two mass and heat energy conservative, unconditionally stable, decoupled numerical algorithms for solving the Cahn–Hilliard–Navier–Stokes–Darcy–Boussinesq system that models thermal convection of two-phase flows in superposed free flow and porous media. The schemes totally decouple the computation of the Cahn–Hilliard equation, the Darcy equations, the heat equation, the Navier–Stokes equations at each time step, and thus significantly reducing the computational cost. We rigorously show that the schemes are conservative and energy-law preserving. Numerical results are presented to demonstrate the accuracy and stability of the algorithms.
Pattern Selection In The Schnakenberg Equations: From Normal To Anomalous Diffusion,
2022
Missouri University of Science and Technology
Pattern Selection In The Schnakenberg Equations: From Normal To Anomalous Diffusion, Hatim K. Khudhair, Yanzhi Zhang, Nobuyuki Fukawa
Mathematics and Statistics Faculty Research & Creative Works
Pattern formation in the classical and fractional Schnakenberg equations is studied to understand the nonlocal effects of anomalous diffusion. Starting with linear stability analysis, we find that if the activator and inhibitor have the same diffusion power, the Turing instability space depends only on the ratio of diffusion coefficients (Formula presented.). However, smaller diffusive powers might introduce larger unstable wave numbers with wider band, implying that the patterns may be more chaotic in the fractional cases. We then apply a weakly nonlinear analysis to predict the parameter regimes for spot, stripe, and mixed patterns in the Turing space. Our numerical …
Marginal Proportional Hazards Models For Clustered Interval-Censored Data With Time-Dependent Covariates,
2022
Harvard Pilgrim Health Care Institute
Marginal Proportional Hazards Models For Clustered Interval-Censored Data With Time-Dependent Covariates, Kaitlyn Cook, Wenbin Lu, Rui Wang
Statistical and Data Sciences: Faculty Publications
The Botswana Combination Prevention Project was a cluster-randomized HIV prevention trial whose follow-up period coincided with Botswana’s national adoption of a universal test-and-treat strategy for HIV management. Of interest is whether, and to what extent, this change in policy (i) modified the observed preventative effects of the study intervention and (ii) was associated with a reduction in the population-level incidence of HIV in Botswana. To address these questions, we propose a stratified proportional hazards model for clustered intervalcensored data with time-dependent covariates and develop a composite expectation maximization algorithm that facilitates estimation of model parameters without placing parametric assumptions on …
Identification Of Disease Resistance Parents And Genome-Wide
Association Mapping Of Resistance In Spring Wheat,
2022
University of Alberta
Identification Of Disease Resistance Parents And Genome-Wide Association Mapping Of Resistance In Spring Wheat, Muhammad Iqbal, Kassa Semagn, Diego Jarquin, Harpinder Randhawa, Brent D. Mccallum, Reka Howard, Reem Aboukhaddour, Izabela Ciechanowska, Klaus Strenzke, José Crossa, J. Jesus Céron-Rojas, Amidou N’Diaye, Curtis Pozniak, Dean Spaner
Department of Statistics: Faculty Publications
The likelihood of success in developing modern cultivars depend on multiple factors, including the identification of suitable parents to initiate new crosses, and characterizations of genomic regions associated with target traits. The objectives of the present study were to (a) determine the best economic weights of four major wheat diseases (leaf spot, common bunt, leaf rust, and stripe rust) and grain yield for multi-trait restrictive linear phenotypic selection index (RLPSI), (b) select the top 10% cultivars and lines (hereafter referred as genotypes) with better resistance to combinations of the four diseases and acceptable grain yield as potential parents, and (c) …
Exploring The Vulnerability Of A Neural Tangent Generalization Attack (Ntga) - Generated Unlearnable Cifar-10 Dataset,
2022
University of South Florida
Exploring The Vulnerability Of A Neural Tangent Generalization Attack (Ntga) - Generated Unlearnable Cifar-10 Dataset, Gitte Ost
USF Tampa Graduate Theses and Dissertations
Nowadays, a massive amount of data is generated and stored on servers and cloudsfrom various applications daily. Preventing these data from unauthorized use often becomes necessary and critical in various real-world applications. Many researchers have studied this crucial problem and developed different methods for this purpose. Among them, Neural Tangent Generalization Attack (NTGA) is one of the most efficient methods to make a dataset unlearnable, which means that the dataset is not learnable by machine learning/deep learning methods. That is, the NTGA-generated dataset is protected against unauthorized use. In this thesis, we explore the vulnerability of an NTGA-generated unlearnable CIFAR-10 …
Antibody Prevalence And Risk Factors Associated With Rickettsia Spp. In A Pediatric Cohort: Sfgr Remains Underdiagnosed And Underreported In El Salvador,
2022
University of South Carolina - Columbia
Antibody Prevalence And Risk Factors Associated With Rickettsia Spp. In A Pediatric Cohort: Sfgr Remains Underdiagnosed And Underreported In El Salvador, Kyndall C. Dye-Braumuller, Marvin Stanley Rodríguez Aquino, Kia Zellars, Hanna Waltz, Madeleine Meyer, Lídua Gual-Gonzalez, Stella C.W. Self, Mufaro Kanyangarara, Melissa Nolan Ph.D., Mph
Faculty Publications
Spotted fever group rickettsioses (SFGR) are caused by a group of tick-borne pathogens that are increasing in incidence globally. These diseases are typically underreported and undiagnosed in low- and middle-income countries, and thus, have been classified as neglected bacterial pathogens. Countries with high poverty, low human development index score, and limited health infrastructure—like El Salvador in Central America—lack necessary surveillance for SFGR and other tick-borne pathogens. This paucity of baseline SFGR infection prevalence leaves vulnerable populations at risk of misdiagnosis. Further, tick-borne disease burdens in El Salvador are severely limited. To lay the foundation for tick-borne disease epidemiology in El …
Process Evaluation Methods And Results From The Health In Pregnancy And Postpartum (Hipp) Randomized Controlled Trial,
2022
University of South Carolina
Process Evaluation Methods And Results From The Health In Pregnancy And Postpartum (Hipp) Randomized Controlled Trial, Sarah Wilcox Phd, Alicia A. Dahl, Alycia K. Boutté, Jihong Liu Sc.D., Kelsey Day, Gabrielle Turner-Mcgrievy Ph.D., Rd, Ellen Wingard
Faculty Publications
Background
Excessive gestational weight gain has increased over time and is resistant to intervention, especially in women living with overweight or obesity. This study described the process evaluation methods and findings from a behavioral lifestyle intervention for African American and white women living with overweight and obesity that spanned pregnancy (≤ 16 weeks gestation) through 6 months postpartum.
Methods
The Health in Pregnancy and Postpartum (HIPP) study tested a theory-based behavioral intervention (vs. standard care) to help women (N = 219; 44% African American, 29.1 ± 4.8 years) living with overweight or obesity meet weight gain guidelines in pregnancy and …
Association Between Use Of Remdesivir And Bradycardia,
2022
University of South Florida
Association Between Use Of Remdesivir And Bradycardia, Gibret Umeukeje
USF Tampa Graduate Theses and Dissertations
Remdesivir received the first emergency use authorization from the FDA for the treatment of COVID-19. Multiple adverse drug reactions (ADR) have been reported since its approval in October 2020. Bradycardia, defined by a decrease in heart rate has been reported as an adverse event for patients receiving remdesivir for COVID-19 treatment. The purpose of the research is to systematically investigate the frequency of occurrence of bradycardia in adults receiving remdesivir using clinical data derived from the FDA Adverse Event Reporting System (FAERS) database. Patients receiving remdesivir were compared to those receiving Paxlovid, Regen-Cov, and Dexamethasone for COVID-19 treatment to see …
Higher Adherence To A Mediterranean Diet Is Associated With Improved Insulin Sensitivity And Selected Markers Of Inflammation In Individuals Who Are Overweight And Obese Without Diabetes,
2022
University of South Carolina
Higher Adherence To A Mediterranean Diet Is Associated With Improved Insulin Sensitivity And Selected Markers Of Inflammation In Individuals Who Are Overweight And Obese Without Diabetes, Surbhi Sood, Jack Feehan, Catherine Itsiopoulos, Kirsty Wilson, Magdalena Plebanski, David Scott, James Hébert Scd, Nitin Shivappa Mbbs, Mph, Ph.D., Aya Mousa, Elena S. George, Barbora De Courten
Faculty Publications
Insulin resistance (IR) and chronic low-grade inflammation are risk factors for chronic diseases including type 2 diabetes (T2D) and cardiovascular disease. This study aimed to investigate two dietary indices: Mediterranean Diet Score (MDS) and Dietary Inflammatory Index (DII®), and their associations with direct measures of glucose metabolism and adiposity, and biochemical measures including lipids, cytokines and adipokines in overweight/obese adults. This cross-sectional study included 65 participants (males = 63%; age 31.3 ± 8.5 years). Dietary intake via 3-day food diaries was used to measure adherence to MDS (0–45 points); higher scores indicating adherence. Energy-adjusted DII (E-DII) scores were calculated with …
The Impact Of Meal Dietary Inflammatory Index On Exercise-Induced Changes In Airway Inflammation In Adults With Asthma,
2022
University of South Carolina
The Impact Of Meal Dietary Inflammatory Index On Exercise-Induced Changes In Airway Inflammation In Adults With Asthma, Katrina P. Mcdiarmid, Lisa G. Wood, John W. Upham, Lesley K. Macdonald-Wicks, Nitin Shivappa Mbbs, Mph, Ph.D., James R. Hébert Scd, Hayley A. Scott
Faculty Publications
Research suggests exercise may reduce eosinophilic airway inflammation in adults with asthma. The Dietary Inflammatory Index (DII®) quantifies the inflammatory potential of the diet and has been associated with asthma outcomes. This study aimed to determine whether the DII of a meal consumed either before or after exercise influences exercise-induced changes in airway inflammation. A total of 56 adults with asthma were randomised to (1) 30–45 min moderate–vigorous exercise, or (2) a control group. Participants consumed self-selected meals, two hours pre- and two hours post-intervention. Energy-adjusted DII (E-DIITM) was determined for each meal, with meals then characterised as “anti-inflammatory” or …
Evaluating Dimensionality
Reduction For Genomic Prediction,
2022
University of Nebraska-Lincoln
Evaluating Dimensionality Reduction For Genomic Prediction, Vamsi Manthena, Diego Jarquín, Rajeev K. Varshney, Manish Roorkiwal, Girish Prasad Dixit, Chellapilla Bharadwaj, Reka Howard
Department of Statistics: Faculty Publications
The development of genomic selection (GS) methods has allowed plant breeding programs to select favorable lines using genomic data before performing field trials. Improvements in genotyping technology have yielded high-dimensional genomic marker data which can be difficult to incorporate into statistical models. In this paper, we investigated the utility of applying dimensionality reduction (DR) methods as a pre-processing step for GS methods. We compared five DR methods and studied the trend in the prediction accuracies of each method as a function of the number of features retained. The effect of DR methods was studied using three models that involved the …
Evaluating Dimensionality
Reduction For Genomic Prediction,
2022
University of Nebraska-Lincoln
Evaluating Dimensionality Reduction For Genomic Prediction, Vamsi Manthena, Diego Jarquín, Rajeev K. Varshney, Manish Roorkiwal, Girish Prasad Dixit, Chellapilla Bharadwaj, Reka Howard
Department of Statistics: Faculty Publications
The development of genomic selection (GS) methods has allowed plant breeding programs to select favorable lines using genomic data before performing field trials. Improvements in genotyping technology have yielded high-dimensional genomic marker data which can be difficult to incorporate into statistical models. In this paper, we investigated the utility of applying dimensionality reduction (DR) methods as a pre-processing step for GS methods. We compared five DR methods and studied the trend in the prediction accuracies of each method as a function of the number of features retained. The effect of DR methods was studied using three models that involved the …
Metabolome-Wide Associations Of Gestational Weight Gain In Pregnant Women With Overweight And Obesity,
2022
University of South Carolina
Metabolome-Wide Associations Of Gestational Weight Gain In Pregnant Women With Overweight And Obesity, Jin Dai, Nansi S. Boghossian, Mark Sarzynski Ph.D., Faha, Facsm, Feng Luo, Xiaoqian Sun, Jian Li, Oliver Fiehn, Jihong Liu Sc.D., Liwei Chen
Faculty Publications
Excessive gestational weight gain (GWG) is associated with adverse pregnancy outcomes. This metabolome-wide association study aimed to identify metabolomic markers for GWG. This longitudinal study included 39 Black and White pregnant women with a prepregnancy body mass index (BMI) of ≥ 25 kg/m2. Untargeted metabolomic profiling was performed using fasting plasma samples collected at baseline (mean: 12.1 weeks) and 32 weeks of gestation. The associations of metabolites at each time point and changes between the two time points with GWG were examined by linear and least absolute shrinkage and selection operator (LASSO) regression analyses. Pearson correlations between the …
A Pilot Study On The Impact Of The Bumptup® Mobile App On Physical Activity During And After Pregnancy,
2022
Western Kentucky University
A Pilot Study On The Impact Of The Bumptup® Mobile App On Physical Activity During And After Pregnancy, Rachel A. Tinius, Maire M. Blankenship, Allison M. Colao, Gregory S. Hawk, Madhawa Perera, Nancy E. Schoenberg
Statistics Faculty Publications
To combat maternal morbidity and mortality, interventions designed to increase physical activity levels during and after pregnancy are needed. Mobile phone-based interventions show considerable promise, and BumptUp® has been carefully developed to address the lack of exercise among pregnant and postpartum women. The primary goal of this pilot study was to test the potential efficacy of BumptUp® for improving physical activity among pregnant and postpartum women. A randomized controlled clinical trial was performed (N = 35) with women either receiving access to the mhealth app or an educational brochure. Physical activity and self-efficacy for exercise data were collected at baseline …
Utilization Of 18s Ribosomal Rna Lamp For Detecting Plasmodium Falciparum In Microscopy And Rapid Diagnostic Test Negative Patients,
2022
University of South Carolina
Utilization Of 18s Ribosomal Rna Lamp For Detecting Plasmodium Falciparum In Microscopy And Rapid Diagnostic Test Negative Patients, Enoch Aninagyei, Adjoa Agyemang Boakye, Clement Okraku Tettey, Kofi Adjei Nitri, Samuel Ohene Ofori, Comfort Dede Tetteh, Thelma Teley Alphour, Tanko Rufai
Faculty Publications
In this study, Plasmodium falciparum was detected in patients that were declared negative for malaria microscopy and rapid diagnostic test kit (mRDT), using Plasmodium 18s rRNA loop-mediated isothermal amplification (LAMP) technique. The main aim of this study was to assess the usefulness of LAMP assay for detecting pre-clinical malaria, when microscopy and mRDT were less sensitive. DNA was obtained from 100 μL of whole blood using the boil and spin method. Subsequently, the Plasmodium 18s rRNA LAMP assay was performed to amplify the specific Plasmodium 18s rRNA gene. Microscopy and mRDT negative samples [697/2223 (31.2%)] were used for this study. …
Bayesian Analysis For The Lomax Model Using Noninformative Priors,
2022
Anhui Normal University
Bayesian Analysis For The Lomax Model Using Noninformative Priors, Daojiang He, Dongchu Sun, Qing Zhu
Department of Statistics: Faculty Publications
The Lomax distribution is an important member in the distribution family. In this paper, we systematically develop an objective Bayesian analysis of data from a Lomax distribution. Noninformative priors, including probability matching priors, the maximal data information (MDI) prior, Jeffreys prior and reference priors, are derived. The propriety of the posterior under each prior is subsequently validated. It is revealed that the MDI prior and one of the reference priors yield improper posteriors, and the other reference prior is a second-order probability matching prior. A simulation study is conducted to assess the frequentist performance of the proposed Bayesian approach. Finally, …
Examining The Association Between A Modified Quan Charlson Comorbidity Index (Qcci) And Viral Suppression: A Cross Sectional Analysis Of Dc Cohort Participants,
2022
George Washington University
Examining The Association Between A Modified Quan Charlson Comorbidity Index (Qcci) And Viral Suppression: A Cross Sectional Analysis Of Dc Cohort Participants, Hasmin C. Ramirez, Lauren O’Connor, Morgan Byrne, Anne Monroe
Epidemiology Faculty Posters and Presentations
No abstract provided.
Quality Of Life In Older And Younger People With Hiv And Diabetes,
2022
George Washington University
Quality Of Life In Older And Younger People With Hiv And Diabetes, Lauren F. O’Connor, La’Marcus Wingate, Sam Simmens, Amanda D. Castel, Anne K. Monroe
Epidemiology Faculty Posters and Presentations
No abstract provided.
(Si10-083) Approximate Controllability Of Infinite-Delayed Second-Order Stochastic Differential Inclusions Involving Non-Instantaneous Impulses,
2022
University of Delhi
(Si10-083) Approximate Controllability Of Infinite-Delayed Second-Order Stochastic Differential Inclusions Involving Non-Instantaneous Impulses, Shobha Yadav, Surendra Kumar
Applications and Applied Mathematics: An International Journal (AAM)
This manuscript investigates a broad class of second-order stochastic differential inclusions consisting of infinite delay and non-instantaneous impulses in a Hilbert space setting. We first formulate a new collection of sufficient conditions that ensure the approximate controllability of the considered system. Next, to investigate our main findings, we utilize stochastic analysis, the fundamental solution, resolvent condition, and Dhage’s fixed point theorem for multi-valued maps. Finally, an application is presented to demonstrate the effectiveness of the obtained results.
