Medicine and Health Sciences Commons^™

Application Of Mixture Models For Doubly Inflated Count Data, Monika Arora, N. Rao Chaganty

Mathematics & Statistics Faculty Publications

In health and social science and other fields where count data analysis is important, zero-inflated models have been employed when the frequency of zero count is high (inflated). Due to multiple reasons, there are scenarios in which an additional count value of k > 0 occurs with high frequency. The zero- and k-inflated Poisson distribution model (ZkIP) is more appropriate for such situations. The ZkIP model is a mixture distribution with three components: degenerate distributions at 0 and k count and a Poisson distribution. In this article, we propose an alternative and computationally fast expectation–maximization (EM) algorithm to obtain the parameter …

Analysis Of Multi-Drug Resistant Mycobacterium Tuberculosis Using Split Deoxyribozymes, Abryana Fergus

Electronic Theses and Dissertations, 2020-2023

Globally, tuberculosis, a disease caused by the species of Mycobacterium tuberculosis (Mtb) complex, stands as a leading cause of death from a single infectious agent. Even though antituberculous drugs are available, treatment is challenging due to antibiotic resistance associated with point mutations in the bacterial genome. Resistance to the first-line antibiotics – rifampin and isoniazid – results in multidrug-resistant tuberculosis (MDR) requiring a more complicated treatment regimen. Timely and accurate identification of drug-resistant TB cases can help prescribe the most effective treatment and prevent the spread of infection. This research aims to develop an assay to discern multi-drug resistant forms …

An Explainable Deep Learning Prediction Model For Severity Of Alzheimer's Disease From Brain Images, Godwin O. Ekuma

Graduate Theses/Dissertations

Deep Convolutional Neural Networks (CNNs) have become the go-to method for medical imaging classification on various imaging modalities for binary and multiclass problems. Deep CNNs extract spatial features from image data hierarchically, with deeper layers learning more relevant features for the classification application. The effectiveness of deep learning models are hampered by limited data sets, skewed class distributions, and the undesirable "black box" of neural networks, which decreases their understandability and usability in precision medicine applications. This thesis addresses the challenge of building an explainable deep learning model for a clinical application: predicting the severity of Alzheimer's disease (AD). AD …

Massachusetts Prevalence Of Opioid Use Disorder Estimation Revisited: Comparing A Bayesian Approach To Standard Capture-Recapture Methods, Jianing Wang, Nathan Doogan, Katherine L. Thompson, Dana Bernson, Daniel Feaster, Jennifer Villani, Redonna Chandler, Laura F. White, David Kline, Joshua A. Barocas

Statistics Faculty Publications

Background: The National Survey on Drug Use and Health (NSDUH) estimated the prevalence of opioid use disorder (OUD) among the civilian, noninstitutionalized people aged 12 years or older in Massachusetts as 1.2% between 2015 and 2017. Accurate estimation of the prevalence of OUD is critical to the success of treatment and resource planning. Various indirect estimation approaches have been used but are subject to data availability and infrastructure-related issues.

Methods: We used 2015 data from the Massachusetts Public Health Data Warehouse (PHD) to compare the results of two approaches to estimating OUD prevalence in the Massachusetts population. First, we used …

Investigating The Use Of Conversational Agents As Accountable Buddies To Support Health And Lifestyle Change, Ekaterina Uetova, Dympna O'Sullivan, Lucy Hederman, Robert J. Ross

Academic Posters Collection

The poster focuses on the role of conversational agents in promoting health and well-being. Results of the literature review indicate that negative emotions can hinder individuals from taking necessary actions related to their health. The study concludes that understanding and addressing emotional barriers is essential to facilitating early access to health services and improving well-being. The poster outlines plans to investigate motivation strategies, develop a prototype conversational agent based on user study insights and chat log data, and incorporate emotion regulation to effectively manage users' emotional experiences.

How Ai Can Learn From The Law: Putting Humans In The Loop Only On Appeal, I. Glenn Cohen, Boris Babic, Sara Gerke, Qiong Xia,, Theodoros Evgeniou, Klaus Wertenbroch

Faculty Scholarly Works

While the literature on putting a “human in the loop” in artificial intelligence (AI) and machine learning (ML) has grown significantly, limited attention has been paid to how human expertise ought to be combined with AI/ML judgments. This design question arises because of the ubiquity and quantity of algorithmic decisions being made today in the face of widespread public reluctance to forgo human expert judgment. To resolve this conflict, we propose that human expert judges be included via appeals processes for review of algorithmic decisions. Thus, the human intervenes only in a limited number of cases and only after an …

Swosu Research And Scholarly Activity Fair 2023, Swosu Office Of Sponsored Programs

SWOSU Research and Scholarly Activity Fair Programs

On behalf of the members of the University Research and Scholarly Activity Committee (USRAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University (SWOSU) - Welcome to the Thirtieth SWOSU Research and Scholarly Activity Fair! There are 77poster presentations and 2 oral presentations involving over 130 student and faculty researchers, writers, presenters, artists, collaborators, and faculty sponsors encompassing activities from the SWOSU College of Pharmacy; SWOSU School of Nursing & Allied Health Sciences; and SWOSU Departments of Allied Health Sciences; Art, Communication & Theatre; Biological Sciences; Business; Computer Science; Chemistry & Physics; Engineering Technology; Language & Literature; …

Health Care Equity Through Intelligent Edge Computing And Augmented Reality/Virtual Reality: A Systematic Review, Vishal Lakshminarayanan, Aswathy Ravikumar, Harini Sriraman, Sujatha Alla, Vijay Kumar Chattu

Engineering Management & Systems Engineering Faculty Publications

Intellectual capital is a scarce resource in the healthcare industry. Making the most of this resource is the first step toward achieving a completely intelligent healthcare system. However, most existing centralized and deep learning-based systems are unable to adapt to the growing volume of global health records and face application issues. To balance the scarcity of healthcare resources, the emerging trend of IoMT (Internet of Medical Things) and edge computing will be very practical and cost-effective. A full examination of the transformational role of intelligent edge computing in the IoMT era to attain health care equity is offered in this …

Interspecific Oral Rabies Vaccine Bait Competition In The Southeast United States, Wesley C. Dixon, Jacob E. Hill, Richard Chipman, Amy J. Davis, Amy Gilbert, James C. Beasley, Olin E. Rhodes Jr., Guha Dharmarajan

United States Department of Agriculture Wildlife Services: Staff Publications

The United States Department of Agriculture’s National Rabies Management Program (NRMP) has coordinated the use of oral rabies vaccination (ORV) to control the spread of raccoon rabies virus variant west of the Appalachian Mountains since 1997. Working with state and local partners, the NRMP deploys ORV baits containing a rabies vaccine, primarily targeting raccoon populations (Procyon lotor). Bait competition between raccoons and non-target species may limit the effectiveness of ORV programs, but the extent of bait competition remains poorly quantified, particularly in the southeastern United States. We placed placebo ORV baits in bottomland hardwood (n = 637 baits) and upland …

A Mathematical Model Of Juvenile Delinquency In The New York State, Oluwasegun Micheal Ibrahim

Articles

This report presents a mathematical model of juvenile delinquency in the New York State. In particular, we develop a juvenile delinquency system of non-linear differential equations using the mathematical epidemiology framework. In constructing this model, we assume that juvenile delinquency can be studied as a socially infectious disease. The stability of the juvenile delinquency-free equilibrium of the model is examined using the standard non-linear dynamical systems theory technique. We carried out a data fitting based on real-life data from the New York State Criminal Justice Services. The research result reveals that the formulated model conforms with the available data and …

Split Catalytic Probes For The Detection Of Monkeypox Virus, Jaehyun Ahn

Honors Undergraduate Theses

The COVID-19 outbreak highlighted the important role that diagnostic tests play in the healthcare system. To reduce the impact of infectious disease outbreaks, the development of rapid and cost-effective point-of-care-tests (POCTs) is crucial. With the dissemination of the Monkeypox (Mpox) virus, it became a necessity to produce POCTS that are inexpensive and easy to use. This work explored the construction of two colorimetric assays that aim to detect Mpox genetic signatures. One is based on the split-peroxidase-like deoxyribozyme probes (sPDz), while the other utilizes a cascade system of split RNA-cleaving deoxyribozyme (sDz) and peroxidase-like deoxyribozyme (PDz). Both rely on catalytic …

Readiness For Transfer: A Mixed-Methods Study On Icu Transfers Of Care, Soo-Hoon Lee, Clarice Wee, Phillip Phan, Yanika Kowitlawakul, Chee-Kiat Tan, Amartya Mukhopadhyay

Management Faculty Publications

Objective Past studies on intensive care unit (ICU) patient transfers compare the efficacy of using standardised checklists against unstructured communications. Less studied are the experiences of clinicians in enacting bidirectional (send/receive) transfers. This study reports on the differences in protocols and data elements between receiving and sending transfers in the ICU, and the elements constituting readiness for transfer.

Methods Mixed-methods study of a 574-bed general hospital in Singapore with a 74-bed ICU for surgical and medical patients. Six focus group discussions (FGDs) with 34 clinicians comprising 15 residents and 19 nurses, followed by a structured questionnaire survey of 140 clinicians …

Biophysical Interactions Control The Progression Of Harmful Algal Blooms In Chesapeake Bay: A Novel Lagrangian Particle Tracking Model With Mixotrophic Growth And Vertical Migration, Jilian Xiong, Jian Shen, Qubin Qin, Michelle C. Tomlinson, Yinglong J. Zhang, Xun Cai, Fei Yi, Linlin Cui, Margaret R. Mulholland

OES Faculty Publications

Climate change and nutrient pollution contribute to the expanding global footprint of harmful algal blooms. To better predict their spatial distributions and disentangle biophysical controls, a novel Lagrangian particle tracking and biological (LPT-Bio) model was developed with a high-resolution numerical model and remote sensing. The LPT-Bio model integrates the advantages of Lagrangian and Eulerian approaches by explicitly simulating algal bloom dynamics, algal biomass change, and diel vertical migrations along predicted trajectories. The model successfully captured the intensity and extent of the 2020 Margalefidinium polykrikoides bloom in the lower Chesapeake Bay and resolved fine-scale structures of bloom patchiness, demonstrating a reliable …

A Global Comparison Of Marine Chlorophyll Variability Observed In Eulerian And Lagrangian Perspectives, Angela M. Kuhn, Matthew Mazloff, Stephanie Dutkiewicz, Oliver Jahn, Sophie Clayton, Tatiana Rynearson, Andrew D. Barton

OES Faculty Publications

The California Current System is a diatom‐dominated region characterized by seasonal coastal upwelling and additional elevated mesoscale activity. Cyclonic mesoscale eddies in the region trap productive coastal waters with their planktonic communities and transport them offshore with limited interaction with surrounding waters, effectively acting as natural mesocosms, where phytoplankton populations undergo ecological succession as eddies age. This study examines diatom community composition within two mesoscale cyclonic eddies that formed in the same region of the California Current System 2 months apart and in the California Current waters surrounding them. The diatom communities were analyzed in the context of shifting environmental …

Extracting High-Molecular Weight Dna From Cyanobacteria Using Promega's Wizard® Hmw Dna Extraction Kit With A Modified Protocol, Metis, Megan A. Hept, Lesley H. Greene

Chemistry & Biochemistry Faculty Publications

Extraction of high molecular weight (HMW) DNA for long read sequencing with little to no fragmentation and high purity is difficult to acquire from cyanobacterial species. Here we describe a modified method of extraction using Promega's Wizard® HMW DNA Extraction Kit to acquire high molecular weight DNA from cyanobacterial species. The protocol used in the kit is the “3.D. Isolating HMW DNA from Gram-Positive and Gram-Negative Bacteria” protocol. During a key step in the protocol, the lingering remnants of the mucilage layer of the cyanobacterial species is removed, preventing it from sticking to the DNA pellet produced. This customized modification …

Enzymatic Electrochemical Biosensors For Neurotransmitters Detection: Recent Achievements And Trends, Zina Fredj, Baljit Singh Dr., Mohamed Bahri, Peiwu Qin, Mohamad Sawan

Articles

Neurotransmitters (NTs) play a crucial role in regulating the behavioral and physiological functions of the nervous system. Imbalances in the concentrations of NT have been directly linked to various neurological diseases (e.g., Parkinson’s, Huntington’s, and Alzheimer’s disease), in addition to multiple psychotic disorders such as schizophrenia, depression, dementia, and other neurodegenerative disorders. Hence, the rapid and real-time monitoring of the NTs is of utmost importance in comprehending neurological functions and identifying disorders. Among different sensing techniques, electrochemical biosensors have garnered significant interest due to their ability to deliver fast results, compatibility for miniaturization and portability, high sensitivity, and good controllability. …

Business Meeting Report (Secretary's And Treasurer's Report), Academy Editors

Journal of the Arkansas Academy of Science

No abstract provided.

Identifying The Serious Clinical Outcomes Of Adverse Reactions To Drugs By A Multi-Task Deep Learning Framework, Haochen Zhao, Peng Ni, Qichang Zhao, Xiao Liang, Di Ai, Shannon Erhardt, Jun Wang, Yaohang Li, Jiianxin Wang

Computer Science Faculty Publications

Adverse Drug Reactions (ADRs) have a direct impact on human health. As continuous pharmacovigilance and drug monitoring prove to be costly and time-consuming, computational methods have emerged as promising alternatives. However, most existing computational methods primarily focus on predicting whether or not the drug is associated with an adverse reaction and do not consider the core issue of drug benefit-risk assessment-whether the treatment outcome is serious when adverse drug reactions occur. To this end, we categorize serious clinical outcomes caused by adverse reactions to drugs into seven distinct classes and present a deep learning framework, so-called GCAP, for predicting the …

Intergenic Transcription In In Vivo Developed Bovine Oocytes And Pre-Implantation Embryos, Saurav Ranjitkar, Mohammad Shiri, Jiangwen Sun, Xiuchun Tian

Computer Science Faculty Publications

Background

Intergenic transcription, either failure to terminate at the transcription end site (TES), or transcription initiation at other intergenic regions, is present in cultured cells and enhanced in the presence of stressors such as viral infection. Transcription termination failure has not been characterized in natural biological samples such as pre-implantation embryos which express more than 10,000 genes and undergo drastic changes in DNA methylation.

Results

Using Automatic Readthrough Transcription Detection (ARTDeco) and data of in vivo developed bovine oocytes and embryos, we found abundant intergenic transcripts that we termed as read-outs (transcribed from 5 to 15 kb after TES) and …

Enabling Customization Of Discussion Forums For Blind Users, Mohan Sunkara, Yash Prakash, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Online discussion forums have become an integral component of news, entertainment, information, and video-streaming websites, where people all over the world actively engage in discussions on a wide range of topics including politics, sports, music, business, health, and world affairs. Yet, little is known about their usability for blind users, who aurally interact with the forum conversations using screen reader assistive technology. In an interview study, blind users stated that they often had an arduous and frustrating interaction experience while consuming conversation threads, mainly due to the highly redundant content and the absence of customization options to selectively view portions …

Cellbrf: A Feature Selection Method For Single-Cell Clustering Using Cell Balance And Random Forest, Yunpei Xu, Hong-Dong Li, Cui-Xiang Lin, Ruiqing Zheng, Yaohang Li, Jinhui Xu, Jianxin Wang

Computer Science Faculty Publications

Motivation

Single-cell RNA sequencing (scRNA-seq) offers a powerful tool to dissect the complexity of biological tissues through cell sub-population identification in combination with clustering approaches. Feature selection is a critical step for improving the accuracy and interpretability of single-cell clustering. Existing feature selection methods underutilize the discriminatory potential of genes across distinct cell types. We hypothesize that incorporating such information could further boost the performance of single cell clustering. Results

We develop CellBRF, a feature selection method that considers genes’ relevance to cell types for single-cell clustering. The key idea is to identify genes that are most important for discriminating …

An Approach To Developing Benchmark Datasets For Protein Secondary Structure Segmentation From Cryo-Em Density Maps, Thu Nguyen, Yongcheng Mu, Jiangwen Sun, Jing He

Computer Science Faculty Publications

More and more deep learning approaches have been proposed to segment secondary structures from cryo-electron density maps at medium resolution range (5--10Å). Although the deep learning approaches show great potential, only a few small experimental data sets have been used to test the approaches. There is limited understanding about potential factors, in data, that affect the performance of segmentation. We propose an approach to generate data sets with desired specifications in three potential factors - the protein sequence identity, structural contents, and data quality. The approach was implemented and has generated a test set and various training sets to study …

Progenitor Cell Isolation From Mouse Epididymal Adipose Tissue And Sequencing Library Construction, Qianglin Liu, Chaoyang Li, Yuxia Li, Leshan Wang, Xujia Zhang, Buhao Deng, Peidong Gao, Mohammad Shiri, Fozi Alkaifi, Junxing Zhao, Jacqueline M. Stephens, Constantine A. Simintiras, Joseph Francis, Jiangwen Sun, Xing Fu

Computer Science Faculty Publications

Here, we present a protocol to isolate progenitor cells from mouse epididymal visceral adipose tissue and construct bulk RNA and assay for transposase-accessible chromatin with sequencing (ATAC-seq) libraries. We describe steps for adipose tissue collection, cell isolation, and cell staining and sorting. We then detail procedures for both ATAC-seq and RNA sequencing library construction. This protocol can also be applied to other tissues and cell types directly or with minor modifications.

For complete details on the use and execution of this protocol, please refer to Liu et al. (2023).¹

*¹ Liu, Q., Li, C., Deng, B., Gao, P., …

A Secure Emr Sharing System With Tamper Resistance And Expressive Access Control, Shengmin Xu, Jianting Ning, Yingjiu Li, Yinghui Zhang, Guowen Xu, Xinyi Huang, Robert H. Deng

Research Collection School Of Computing and Information Systems

To reduce the cost of human and material resources and improve the collaborations among medical systems, research laboratories and insurance companies for healthcare researches and commercial activities, electronic medical records (EMRs) have been proposed to shift from paperwork to friendly shareable electronic records. To take advantage of EMRs efficiently and reduce the cost of local storage, EMRs are usually outsourced to the remote cloud for sharing medical data with authorized users. However, cloud service providers are untrustworthy. In this paper, we propose an efficient, secure, and flexible EMR sharing system by introducing a novel cryptosystem called dual-policy revocable attribute-based encryption …

Hart, Robert W., Papers, 1924-1966, Special Collections, Leonard H. Axe Library

Finding Aids

Personal documents, correspondence, and financial records of Robert W. Hart, former professor at Pittsburg State University.

Robert William Hart was born in 1896 to William and Sarah Hart and grew up in Crawford County, Kansas. In 1916 he graduated from the State Manual Training Normal School (now Pittsburg State University), and found early work as an engineer. Robert served as an ensign in the navy during World War I. He taught in the public schools in Fort Scott and Pittsburg from 1916-1918; 1921-1923. In 1920 he married Retta Statler and they had two children. In 1923 he was hired as …

Occupational Risk Perceptions Among Foreign-Born Construction Workers In Central Florida, Matthew Edison Law

Walden Dissertations and Doctoral Studies

Hispanic and Latino foreign-born construction workers in the United States experience higher rates of serious injuries and fatalities in the workplace than their native-born peers. Previous research has pointed to specific vulnerabilities among this population, including birthplace, age of the worker, language barriers, and education level, but little to no research has examined addressable risk factors, such as occupational risk perceptions, among this population. The purpose of this quantitative study was to determine the relationship between birthplace, number of years working in the United States, and occupational risk perceptions while controlling for age of the worker, language barriers, and education …

The Daily Patterns Of Emergency Medical Events, Mary Elizabeth Helander, Margaret K. Formica, Dessa K. Bergen-Cico

Social Science - All Scholarship

This study examines population level daily patterns of time-stamped emergency medical service (EMS) dispatches to establish their situational predictability. Using visualization, sinusoidal regression, and statistical tests to compare empirical cumulative distributions, we analyzed 311,848,450 emergency medical call records from the U.S. National Emergency Medical Services Information System (NEMSIS) for years 2010 through 2022. The analysis revealed a robust daily pattern in the hourly distribution of distress calls across 33 major categories of medical emergency dispatch types. Sinusoidal regression coefficients for all types were statistically significant, mostly at the p < 0.0001 level. The coefficient of determination ($R^2$) ranged from 0.84 and 0.99 for all models, with most falling in the 0.94 to 0.99 range. The common sinusoidal pattern, peaking in mid-afternoon, demonstrates that all major categories of medical emergency dispatch types appear to be influenced by an underlying daily rhythm that is aligned with daylight hours and common sleep/wake cycles. A comparison of results with previous landmark studies revealed new and contrasting EMS patterns for several long-established peak occurrence hours--specifically for chest pain, heart problems, stroke, convulsions and seizures, and sudden cardiac arrest/death. Upon closer examination, we also found that heart attacks, diagnosed by paramedics in the field via 12-lead cardiac monitoring, followed the identified common daily pattern of a mid-afternoon peak, departing from prior generally accepted morning tendencies. Extended analysis revealed that the normative pattern prevailed across the NEMSIS data when re-organized to consider monthly, seasonal, daylight-savings vs civil time, and pre-/post- COVID-19 periods. The predictable daily EMS patterns provide impetus for more research that links daily variation with causal risk and protective factors. Our methods are straightforward and presented with detail to provide accessible and replicable implementation for researchers and practitioners.

Climate Change And The Law Of National Security Adaptation, Mark P. Nevitt

Faculty Articles

The Department of Defense (DoD) is the largest employer in the world, owns and operates an enormous global real estate portfolio, and emits more Greenhouse Gases (GHGs) than many nations. Entrusted with the national security, the DoD is now threatened by a new enemy—climate change. Climate change imperils national security infrastructure while undermining the military’s capacity to respond to climate-driven disasters at home and abroad. However, legal scholarship has yet to address what I call “the law of national security adaptation” and related questions. For example, how do environmental and climate change laws apply to the U.S. military? What laws …

Modeling The Spread Of Covid-19 In Spatio-Temporal Context, S.H. Sathish Indika, Norou Diawara, Hueiwang Anna Jeng, Bridget D. Giles, Dilini S.K. Gamage

Mathematics & Statistics Faculty Publications

This study aims to use data provided by the Virginia Department of Public Health to illustrate the changes in trends of the total cases in COVID-19 since they were first recorded in the state. Each of the 93 counties in the state has its COVID-19 dashboard to help inform decision makers and the public of spatial and temporal counts of total cases. Our analysis shows the differences in the relative spread between the counties and compares the evolution in time using Bayesian conditional autoregressive framework. The models are built under the Markov Chain Monte Carlo method and Moran spatial correlations. …

Changes In Running Biomechanics In Master Runners Over Age 50: A Systematic Review, Matthew Klein, Chris Patterson

Faculty Publications - College of Physical Therapy

The number of individuals over 50 years of age participating in recreational and competitive running has increased over the past ten years. It has been established that older runners experience a reduction in strength and power. These changes may contribute to different running biomechanics from younger runners. The pur-pose of this study was to synthesise the current evidence on run-ning biomechanical differences in the lower extremity between masters runners over 50 years and younger runners under 40 years. The systematic data search included CINAHL, MEDLINE, and SPORTDiscus databases. Fourteen cross-sectional studies that com-pared lower extremity biomechanics of masters runners to …