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Seshaiyer: Data-Driven Machine Learning Framework To Predict Dynamics Of Infectious Diseases Incorporating Human Behavior, Alonso Gabriel Ogueda Oliva, Dr. Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Improving Infectious Disease Predictions Through The Use Of Metapopulation Sir Modeling And Graph Convolutional Neural Networks, Petr Kisselev, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Cure Rate Analysis Of National Health Insurance Scheme Claims Payment Survival Times In Ghana: The Case Of Pru District, Ahmed Tamimu, Suleman Nasiru, Dioggban Jakperik

Al-Bahir

In this study, cure models have been applied to model National Health Insurance Scheme (NHIS) claims payment data with cured proportion using Pru District in the Bono East Region of Ghana as a case study. The covariates effects were also modelled to investigate the effects of the covariates on the cured proportion. The estimates of the parameters of the models were obtained by directly maximizing the observed likelihood functions. Most estimates of the parameters of the cure models are significant at 5% significance level. The study revealed that the cured claims payments rate increases over time with an estimated cured …

Advancing Crispr-Based Solutions For Covid-19 Diagnosis And Therapeutics, Roaa Hadi, Abhishek Poddar, Shivakuma Sonnaila, Venkata Suryanarayana Murthy Bhavaraju, Shilpi Agrawal

Chemistry & Biochemistry Faculty Publications and Presentations

Since the onset of the COVID-19 pandemic, a variety of diagnostic approaches, including RT-qPCR, RAPID, and LFA, have been adopted, with RT-qPCR emerging as the gold standard. However, a significant challenge in COVID-19 diagnostics is the wide range of symptoms presented by patients, necessitating early and accurate diagnosis for effective management. Although RT-qPCR is a precise molecular technique, it is not immune to false-negative results. In contrast, CRISPR-based detection methods for SARS-CoV-2 offer several advantages: they are cost-effective, time-efficient, highly sensitive, and specific, and they do not require sophisticated instruments. These methods also show promise for scalability, enabling diagnostic tests. …

Learning Problems Related To Stochastic Differential Equations, Jinpu Zhou

LSU Doctoral Dissertations

Stochastic differential equations (SDEs) are essential for modeling systems influenced by both deterministic dynamics and random fluctuations, with applications in a wide variety of disciplines. This thesis develops a Bayesian framework for nonparametric learning in SDEs, addressing key challenges in inference, particularly when dealing with complex systems and incomplete data. The thesis begins by establishing a theoretical foundation in optimization over Hilbert spaces, including a generalized representer theorem to address infinite-dimensional optimization problems encountered in nonparametric inference. Building on this, we introduce a Bayesian framework with shrinkage priors to learn drift functions from high-frequency data. Bayesian approach incorporates low-cost sparse …

Noncontact Diffuse Reflectance Spectroscopy Of Synovial Fluid Samples For Rapid Identification Of Infections, Erin E. Drewke, Robert L. Brand, Caroline G. Geels, Hanna K. Jensen, Kevin Wong, Jarret D. Sanders, Narasimhan Rajaram

Biomedical Engineering Faculty Publications and Presentations

Severe joint infections, such as septic arthritis, require rapid diagnostic testing of the synovial fluid aspirated from joints level so that a surgical team can be assembled quickly. We present a diffuse reflectance spectroscopy (DRS) system for noncontact determination of infection. Using a light-tight syringe holder and fiber optic probe, diffusely reflected light from 475 to 655 nm was acquired from 18 patient samples through the wall of a syringe in a noncontact and sterile manner. We determined the reflectance ratios at two different wavelengths—R ₄₉₀/R ₆₀₀ and R ₅₈₀/R ₆₀₀ and found statistically significant …

Empowering Modernization Of National Emergency Management With New Generation Of Information Technology: Technology Foresight And Policy Recommendations Based On Typical Scenarios, Haibo Zhang, Xinyu Dai, Yi Peng, Yi Liu, Xue Lin, Yongjian Zhu, Wu Chen, Zhen Wu, Xinyue Qin, Depei Qian, Jian Lv

Bulletin of Chinese Academy of Sciences (Chinese Version)

In the context of the new round of scientific and technological revolution, how to grasp the historical opportunity of supporting the development of the “overall safety and emergency response framework” with the NGIT, and promoting the transformation of the public safety governance to emphasis on prevention, is a pressing issue to be studied. This study focuses on five typical scenarios in emergency management, drawing on multiple rounds of expert interviews and questionnaire surveys to identify a list of critical technologies, analyze future development trends and constraints, and provide references for advancing relevant technological research and development. The study further emphasizes …

Essays On Information Technology In Healthcare, Gleb Zavadskiy

USF Tampa Graduate Theses and Dissertations

Information technologies (IT) and information systems (IS) have profound significance across various sectors of society, including healthcare, business, education, government, and beyond. First, IT facilitates instant communication globally through email, messaging apps, video conferencing, and social media, revolutionizing how individuals and organizations interact, collaborate, and share information (Hacker et al. 2020; Tang and Hew 2020).

Secondly, the Internet and digital libraries provide worldwide access to vast amounts of information, what makes knowledge and education available to everyone, empowering individuals to learn and stay informed on diverse topics (Haleem et al. 2022). Another aspect of IT systems in various industries is …

Festival Of Research Abstracts, Fall 2024, College Of Science And Mathematics, Wright State University

Festival of Research

The collection of abstracts accepted for the Fall 2024 Festival of Research hosted by the Wright State University College of Science and Mathematics.

Assessing The Impact Of Femur Morphological Variations On Pediatric Hip Joint Biomechanics Using Statistical Shape Modeling, Tamara Chambers

Doctoral Dissertations and Master's Theses

This dissertation aimed to (1) quantify morphological variations in the pediatric hip joint and (2) evaluate the sensitivity of an infant musculoskeletal model (MSM) to these variations, considering hip joint center estimation errors. A shape statistical model (SSM) of decedent infant femurs from the Ortolani collection was created using ShapeWorks, capturing key morphological features, such as variations in the femoral neck-shaft and anteversion angles. Seven synthetic femurs were generated from the SSM to create SSM-informed MSMs, which were systematically evaluated through kinematics and kinetics analyses in OpenSim. Incorporating the SSM led to slight changes in the pediatric MSMs’ kinematics but …

Remediation Technology And Study To Remove Nano-Pollutants From Wastewater, Lauretta Ngozi Ndu Nwagu

Dissertations (2016-Present)

Life on Earth depends on water, which also has a direct impact on climate, health, and economic growth. Water poverty, pollution, and scarcity are some of the environmental issues confronting our society today. Water pollution and water poverty are both measurable parameters. Water quality is measured by comparing its physical, chemical, and biological properties to a predefined standard. This study examines remediation techniques for removing nano-pollutants from human-generated wastewater. In order to satisfy the Environmental Protection Agency’s (EPA) standard, this technological approach utilizes gravity and a zero-carbon footprint for wastewater purification.

The research is designed with various pore sizes of …

Bayesian Nonparametric Models For Pooled Data, Yizeng Li

Theses and Dissertations

This work examines two applications of pooling: group testing and pooled biomonitoring. Group testing, introduced by Dorfman in the early 1940s, was initially developed to screen for syphilis among U.S. inductees during World War II. Since then, the approach has demonstrated cost-saving benefits in diverse fields, including drug discovery, genetics, and infectious disease testing. While various regression methods—parametric, nonparametric, and semiparametric—have been proposed to analyze group testing data, they fall short in addressing age-related disparities in disease presence if such variations exist. In Chapter 2, we address this gap by expanding varying coefficient regression within a Bayesian framework to accommodate …

Meta-Analysis Of Censored Adverse Events, Xinyue Qi, Shouhao Zhou, Christine B Peterson, Yucai Wang, Xinying Fang, Michael L Wang, Chan Shen

Faculty, Staff and Student Publications

Meta-analysis is a powerful tool for assessing drug safety by combining treatment-related toxicological findings across multiple studies, as clinical trials are typically underpowered for detecting adverse drug effects. However, incomplete reporting of adverse events (AEs) in published clinical studies is frequently encountered, especially if the observed number of AEs is below a pre-specified study-dependent threshold. Ignoring the censored AE information, often found in lower frequency, can significantly bias the estimated incidence rate of AEs. Despite its importance, this prevalent issue in meta-analysis has received little statistical or analytic attention in the literature. To address this challenge, we propose a Bayesian …

Using Machine Learning And Deep Learning Algorithms To Improve Low Birthweight Prediction, Yang Ren

Theses and Dissertations

Low birthweight (LBW) is a major public health issue resulting in increased neonatal mortality and long-term health complications. Traditional LBW analysis methods, focusing on incidence rates and risk factors through statistical models, often struggle with complex unseen data, and thus, their effectiveness is limited in early prevention of LBW, requiring more advanced LBW prediction models. Therefore, this dissertation delves into this important research area by proposing and examining novel machine learning (ML) and deep learning (DL) algorithms, aiming to predict LBW more accurately during the early stage of pregnancy. This dissertation consists of three studies, strategically designed to build upon …

A Coupled Spatial-Network Model: A Mathematical Framework For Applications In Epidemiology, Hannah Kravitz, Christina Duron, Moysey Brio

Mathematics and Statistics Faculty Publications and Presentations

There is extensive evidence that network structure (e.g., air transport, rivers, or roads) may significantly enhance the spread of epidemics into the surrounding geographical area. A new compartmental modeling framework is proposed which couples well-mixed (ODE in time) population centers at the vertices, 1D travel routes on the graph’s edges, and a 2D continuum containing the rest of the population to simulate how an infection spreads through a population. The edge equations are coupled to the vertex ODEs through junction conditions, while the domain equations are coupled to the edges through boundary conditions. A numerical method based on spatial finite …

Isolating Microbes From The Surface Of An Introductory Laboratory Halite Hand Sample, Kesley G. Banks, Michael A. Gibson, Matthew A. Pritchett

The Compass: Earth Science Journal of Sigma Gamma Epsilon

Introductory geology labs stress simple physical testing (luster, hardness, etc.) to identify common minerals, using mineral charts to eliminate minerals not exhibiting a particular property. Special properties (magnetism, specific gravity, taste, etc.) for specific minerals narrows mineral identity. Students often express safety concerns about licking minerals, especially when they realize others have previously licked the specimen. As an exercise in medical geology, we cultured microbes from a halite sample used for nearly 25 years and licked by numerous students over that time span (Sample 1), a commercially purchased unused and freshly exposed surface of halite licked by one person (Sample …

A Framework For Human Evaluation Of Large Language Models In Healthcare Derived From Literature Review, Thomas Yu Chow Tam, Sonish Sivarajkumar, Sumit Kapoor, Alisa V Stolyar, Katelyn Polanska, Karleigh R Mccarthy, Hunter Osterhoudt, Xizhi Wu, Shyam Visweswaran, Sunyang Fu, Piyush Mathur, Giovanni E Cacciamani, Cong Sun, Yifan Peng, Yanshan Wang

Faculty, Staff and Student Publications

With generative artificial intelligence (GenAI), particularly large language models (LLMs), continuing to make inroads in healthcare, assessing LLMs with human evaluations is essential to assuring safety and effectiveness. This study reviews existing literature on human evaluation methodologies for LLMs in healthcare across various medical specialties and addresses factors such as evaluation dimensions, sample types and sizes, selection, and recruitment of evaluators, frameworks and metrics, evaluation process, and statistical analysis type. Our literature review of 142 studies shows gaps in reliability, generalizability, and applicability of current human evaluation practices. To overcome such significant obstacles to healthcare LLM developments and deployments, we …

Ecology Of Tetrodotoxin Toxicity And Ectoparasite Burden Of Hong Kong Newt Populations, Wing Yan Yip

Lingnan Theses (MPhil & PhD)

Many amphibians have defensive chemicals in their skin. Newts from the family Salamandridae possess a potent neurotoxin - tetrodotoxin (TTX). TTX toxicity has been studied intensively, with the aim of revealing the function and origin of TTX in this family. Research has found within- and between-population variations in North American newts like Taricha, possibly related to co-evolution with its predator, symbiotic bacteria, or several life history traits (e.g., sex and life stage). However, our knowledge about TTX ecology in the Asian newt clade is relatively limited. Additionally, a group of water mites, Lurchibates, specifically parasitizes Asian newts, but …

Exploring The Correlation Between Climate Change And Influenza Activity In The Northeast United States, 2003-2023, Emily M. Posadas

Doctoral Dissertations and Projects

The influenza virus is influenced by a myriad of complex interactions with human and environmental factors, with changing climate patterns having significant effects on the health status of a population. This study investigates the correlation between climate change and influenza activity in the northeast United States from 2003 to 2023, providing insight and understanding into the interaction between the two variables. The anthropogenic factors that have contributed to climate change are recognized, and circulating seasonal and avian influenza viruses are discussed within the context of climate change. The investigation of the correlation between climate change and influenza activity across this …

Root Lesion And Burrowing Nematodes And Their Management, Department Of Primary Industries And Regional Development, Western Australia

Grains and other field crops factsheets

Nematodes are common soil pests that feed on the roots of a wide range of crops in all agricultural areas of Western Australia, resulting in significant crop yield loss. Root lesion nematode can be managed but not eradicated.

This factsheet summarises the biology of the root lesion nematode (RLN, Pratylenchus spp.) and burrowing nematode (Radopholus spp.) species that damage Western Australian (WA) crops, and their diagnosis and management.

Putting Gpt-4o To The Sword: A Comprehensive Evaluation Of Language, Vision, Speech, And Multimodal Proficiency, Sakib Shahriar, Brady D. Lund, Nishith Reddy Mannuru, Muhammad Arbab Arshad, Kadhim Hayawi, Ravi Varma Kumar Bevara, Aashrith Mannuru, Laiba Batool

All Works

As large language models (LLMs) continue to advance, evaluating their comprehensive capabilities becomes significant for their application in various fields. This research study comprehensively evaluates the language, vision, speech, and multimodal capabilities of GPT-4o. The study employs standardized exam questions, reasoning tasks, and translation assessments to assess the model’s language capability. Additionally, GPT-4o’s vision and speech capabilities are tested through image classification and object-recognition tasks, as well as accent classification. The multimodal evaluation assesses the model’s performance in integrating visual and linguistic data. Our findings reveal that GPT-4o demonstrates high accuracy and efficiency across multiple domains in language and reasoning …

Data Driven Decision Making For Sustainable Planning And Operations Of Large Scale Networks, Bahareh Kargar

Dissertations

This dissertation explores data-driven decision-making networks, focusing on sustainable planning and operations for large-scale systems such as healthcare supply chains and power systems. One significant application in healthcare is the optimization of vaccine supply chains. An agent-based simulation-optimization modeling framework is developed to enhance the efficiency and sustainability of vaccine distribution. First, an agent-based epidemiological model of COVID-19 is extended to capture disease transmission dynamics and forecast the number of susceptible individuals and infections. Then, a sustainable vaccine supply chain considering the impacts of greenhouse gases is developed and integrated with the simulation model to minimize total costs and environmental …

Molecular Docking, Pharmacological Profiling, And Molecular Dynamics Simulation Of Potential Antihyperuricemic Agent From Secondary Metabolites Of Dillenia Philippinensis Rolfe (Dilleniaceae), Louie Rince C. Suyo, John P. Paulin, Nicole Clarence Louise L. Gapaz, Markus Brent S. Arevalo, Vince Tyrell P. Yongco, Librado A. Santiago

Karbala International Journal of Modern Science

Crystal accumulation in the joints due to increased serum uric acid (sUA) may lead to an inflammatory condition called gout. Increased sUA is caused by the excessive reabsorption of the urate anion transporter-1 (URAT-1). Therefore, URAT-1 inhibition will promote uric acid excretion and reduce the risk of having gout. Dillenia philippinensis Rolfe, often known as katmon, is an endemic plant in the Philippines with bioactive compounds associated with several therapeutic benefits. The present study represents the first scientific inquiry into the antihyperuricemic potential of compounds isolated from D. philippinensis. This study aimed to assess the interaction of URAT-1 with …

Analysis Of The Effect Of Vaccination, Efficient Surveillance And Treatment On The Transmission Dynamics Of Cholera, Loyinmi Adedapo Chris, Ajala Adebisi Shukurat, Alani L. Ijaola

Al-Bahir

In this study, we presented a modified SIR-SI model to investigate the dynamics and potential controls for cholera transmission, with an incident rate equipped with a saturation factor to investigate the combined impact of three vital measures which include effective surveillance, vaccination campaign and proper treatment in case severity. We established among other things, the qualitative analysis of the model to validate the results. Furthermore, the reproduction number (R0) was found to be less than unity (1), through the stability analysis. Additionally, finite different scheme was utilized in solving the differential equations of the model. MATLAB software was used for …

Erlang-Distributed Seir Epidemic Models With Cross-Diffusion, Victoria Chebotaeva

Theses and Dissertations

We examine the effects of cross-diffusion dynamics in epidemiological models. Using reaction-diffusion dynamics to model the spread of infectious diseases, we focus on situations in which the movement of individuals is affected by the concentration of individuals of other categories. In particular, we present a model where susceptible individuals move away from large concentrations of infected and infectious individuals.

Our results show that accounting for this cross-diffusion dynamics leads to a noticeable effect on epidemic dynamics. It is noteworthy that this leads to a delay in the onset of epidemics and an increase in the total number of people infected. …

Mathematical Modeling, Analysis, And Simulation Of Patient Addiction Journey, Adan Baca, Diego Gonzalez, Alonso G. Ogueda, Holly C. Matto, Padmanabhan Seshaiyer

CODEE Journal

This paper aims to develop a mathematical model to study the dynamics of addiction as individuals go through their detox journey. The motivation for this work is three fold. First, there has been a significant increase in drug overdose and drug addiction following the COVID-19 pandemic, and addiction may be interpreted as a infectious disease. Secondly, the dynamics of infectious disease could be modeled via compartmental models described by differential equations and one can therefore leverage the existing analytical and numerical methods to model addiction as a disease. Finally, the work helps to inform how mathematical models governed by differential …

Comprehensive Climate Vulnerability Assessment Of A Regional Karst Landscape For Hazard Mitigation Planning, Kara Brunot

Masters Theses & Specialist Projects

Climate change is the global phenomena affecting all sectors of society by creating conditions more conducive for the occurrence of extreme weather events. It is projected that the intensity and frequency of events will increase. Flooding, in particular, is projected to increase in frequency due to more intense precipitation events. Karst landscapes are especially vulnerable to climate change impacts because of their unique hydrology and geology. Karst flooding is most likely to occur from prolonged or intense rain events, which climate change will likely make more feasible. Areas are disproportionately affected by climate change due to population demographics and environmental …

Lactoferrin And Lysozyme To Promote Nutritional, Clinical And Enteric Recovery: A Protocol For A Factorial, Blinded, Placebo-Controlled Randomised Trial Among Children With Diarrhoea And Malnutrition (The Boresha Afya Trial), Ruchi Tiwari, Kirkby Tickell, Emily Yoshioka, Joyce Otieno, Adeel Shah, Barbra Richardson, Lucia Keter, Maureen Okello, Churchil Nyabinda, Indi Trehan

Paediatrics and Child Health, East Africa

Introduction: Children with moderate or severe wasting are at particularly high risk of recurrent or persistent diarrhoea, nutritional deterioration and death following a diarrhoeal episode. Lactoferrin and lysozyme are nutritional supplements that may reduce the risk of recurrent diarrhoeal episodes and accelerate nutritional recovery by treating or preventing underlying enteric infections and/or improving enteric function.

Methods and analysis: In this factorial, blinded, placebo-controlled randomised trial, we aim to determine the efficacy of lactoferrin and lysozyme supplementation in decreasing diarrhoea incidence and improving nutritional recovery in Kenyan children convalescing from comorbid diarrhoea and wasting. Six hundred children aged 6–24 months with …

Structure-Function Relationships In Neurodegenerative And Infectious Diseases: Biophysical Characterization Of Rna Secondary Structures By Computational Techniques, Kendy Guarinoni

Electronic Theses and Dissertations

The research described in this dissertation focuses on the investigation of the structure and dynamics of regions of RNA implicated in two diseases: COVID-19 and amyotrophic lateral sclerosis/frontotemporal dementia (ALS/FTD). Both studies sought to create experimentally corroborated models that were used to characterize the structure and dynamics of the C9orf72 repeat expansion and the s2m region in coronaviruses, respectively and provided the foundation for future work. In our work involving the s2m region of SARS-CoV-2, the virus responsible for COVID-19, we determined that the homology modeling approach commonly used to derive atomistic structures when no coordinates are available yields a …

Antimicrobial And Chemical Characterization Of Cold Atmospheric-Pressure Plasmas, Dalton Albert Miller

Boise State University Theses and Dissertations

Microbial contamination of food processing facilities is a major cause of human disease and economic loss. There are approximately 48,000,000 cases of foodborne illness in the United States annually, leading to 128,000 hospitalizations and 1,300 deaths. The total economic damages are estimated at $36 billion each year, including productive hours, medical expenses, and the disposal of contaminated foodstuffs. Current methods to reduce contamination on food processing surfaces utilize steam or concentrated chemicals (hydrogen peroxide, hypochlorite, strong acids, strong bases) that are hazardous to workers and required large volumes of water to remove prior to resuming contact with food. Ongoing outbreaks …