Digital Commons Network^™

Issue 41

The Synapse: Intercollegiate science magazine

No abstract provided.

The Care Crisis: The Neurology Of Dementia And International Solutions, Sophie Paton

The Synapse: Intercollegiate science magazine

No abstract provided.

Will My Celsius Addiction Kill Me?: The Thermogenic Drink And Its Impact On Nutrition And Metabolism, Katie Johnstone

The Synapse: Intercollegiate science magazine

No abstract provided.

Genes And Zzz's: The Genetic Variations Of Sleep Disorders, Ananya Sivasubramaniam

The Synapse: Intercollegiate science magazine

No abstract provided.

Invisible Intruders: The Growing Presence Of Microplastics And Its Effects On The Brain, Megan Carlson

The Synapse: Intercollegiate science magazine

No abstract provided.

Peeling Back Allergies: Punica Granatum And Its Various Bene.Its, Mina Stalhamer, Haimanot Assefa

The Synapse: Intercollegiate science magazine

No abstract provided.

Quantifying Greenhouse Gas Exchange And Ecosystem Services In Ecosystems Managed For Nature-Based Solutions Using Eddy Covariance, Remote Sensing, And Models, Lucas Clay

All Dissertations

As global temperatures rise due to climate change, nature-based solutions are increasingly being used to restore nature and to remove carbon from the atmosphere. Nature-based solutions draw on methodologies such as ecological forestry and improved forest management to reduce emissions and maximize resilience. These protocols are still in their infancy and additional measurements and case studies are important to optimizing these protocols. Herein this dissertation we describe multiple measurement methodologies for both greenhouse gas (GHG) emissions and for ecosystem services. In coastal wetland ecosystems, the need for GHG measurements is paramount to understanding the ability of these ecosystems to reduce …

Quantile Regression And Change Point Analysis Of Remote Patient Monitoring Data From Cardiomems Hf System, Shanshan Jia

All Dissertations

Quantile regression provides a sophisticated analytical approach for clinical data, offering deeper insights into patient variability and risk assessment than conventional regression techniques. This study delves into the mathematical underpinnings of quantile regression, highlighting its advantages over ordinary least squares (OLS) regression, particularly in the context of predicting diastolic pulmonary artery pressure (PAP). We explore how this method can be applied to guide clinical interventions more effectively. By leveraging quantile regression’s ability to model different parts of the outcome distribution, we demonstrate its potential to enhance patient care through improved identification of high-risk individuals and the development of more personalized …

Cross-Interactions Of Amyloid Proteins: Implications For Aggregation Dynamics And Disease Pathology, Zhiyuan Song

All Dissertations

Amyloid aggregation is a pervasive form of protein misfolding implicated in the pathology of several prominent human diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and type 2 diabetes (T2D). These diseases are marked by the accumulation of amyloid fibrils and toxic oligomers, which are highly dynamic and heterogeneous, posing challenges for understanding their roles in disease progression. Despite significant advances in the diagnosis and management of these conditions, no definitive cure is available. We investigate amyloid aggregation and cross-seeding, with a focus on amyloid-beta (Aβ), tau, alpha-synuclein (αS), and human islet amyloid polypeptide (IAPP) through discrete molecular dynamics (DMD) …

Agricultural Water Use In South Carolina - A Series Of Investigations To Support Long-Term Planning, Charles Pellett

All Dissertations

Agricultural water use in South Carolina has been the subject of some public debate. While there are several sources of information available, the accuracy of the relevant data has been called into doubt. Self-reported estimates may be biased; survey sampling and extrapolation methods yield wide ranges of uncertainty; and reporting compliance or response rate can change over time.

Agricultural water users self-report that their estimates of water use volumes are less accurate than the other major sectors of water use. Center pivot irrigation is the largest and fastest growing kind of agricultural water use in SC. Since the year 2000, …

Traittrainr: Accelerating Large-Scale Simulation Under Models Of Continuous Trait Evolution, Jenniffer Roa Lozano, Mataya Duncan, Duane D. Mckenna, Todd A. Castoe, Michael Degiorgio, Richard Adams

Entomology and Plant Pathology Faculty Publications and Presentations

Abstract

The scale and scope of comparative trait data are expanding at unprecedented rates, and recent advances in evolutionary modeling and simulation sometimes struggle to match this pace. Well-organized and flexible applications for conducting large-scale simulations of evolution hold promise in this context for understanding models and more so our ability to confidently estimate them with real trait data sampled from nature. Results

We introduce TraitTrainR, an R package designed to facilitate efficient, large-scale simulations under complex models of continuous trait evolution. TraitTrainR employs several output formats, supports popular trait data transformations, accommodates multi-trait evolution, and exhibits flexibility …

A Shared Mechanism For Tnp-Atp Recognition By Members Of The P2x Receptor Family, Xiao-Bo Ma, Chen-Xi Yue, Yan Liu, Yang Yang, Jin Wang, Xiao-Na Yang, Li-Dong Huang, Michael X Zhu, Motoyuki Hattori, Chang-Zhu Li, Ye Yu, Chang-Run Guo

Faculty, Staff and Student Publications

P2X receptors (P2X1-7) are non-selective cation channels involved in many physiological activities such as synaptic transmission, immunological modulation, and cardiovascular function. These receptors share a conserved mechanism to sense extracellular ATP. TNP-ATP is an ATP derivative acting as a nonselective competitive P2X antagonist. Understanding how it occupies the orthosteric site in the absence of agonism may help reveal the key allostery during P2X gating. However, TNP-ATP/P2X complexes (TNP-ATP/human P2X3 (hP2X3) and TNP-ATP/chicken P2X7 (ckP2X7)) with distinct conformations and different mechanisms of action have been proposed. Whether these represent species and subtype variations or experimental differences remains unclear. Here, we show …

Heavy Metals In Rural Soils: A Case Study In Jennings County, Indiana, Madeline Hill

All-Inclusive List of Electronic Theses and Dissertations

Heavy metals, such as lead and mercury, can be toxic if exposure levels are too high. People are often concerned about lead exposure from water or paint, but soil is another potential exposure avenue for many metals. While some heavy metals, including mercury and lead, are found in emissions from coal-burning power plants and from incinerators, many metals accumulate in soils from past uses (ex. lead paint, leaded gasoline, chemical spills, industrial emissions, and natural occurrences). It is important to have soil tested to check metal concentrations because consumption or inhalation of these metals can lead to permanent damage and …

The Relationship Between Salvinia Molesta Infestation And The Microbial Ecology Of Wetlands At Caddo Lake, Tx, Usa, Martin Hadsell

Electronic Theses and Dissertations

Wetlands are known to host many beneficial geochemical processes such as nutrient cycling and carbon sequestration. These processes are primarily driven by the microbial communities within a wetland. The establishment of non-native invasive species within wetlands has the potential to alter the once beneficial functionality of wetland microbial communities due to the sensitivity microbes have towards environmental changes. Because of this, several metagenomic studies have been conducted to assess microbial community response to aquatic plant invasion; however, there haven’t been any studies researching the influence of Salvinia molesta (D.S. Mitch.), commonly known as Giant Salvinia, on microbial communities. The goal …

Bioremediation Of Effluent Water In A Coal Ash Disposal Area: Optimizing Microbial Sulfate Reduction, Ryka Shea

Electronic Theses and Dissertations

Coal combustion residues (CCR) pose a serious environmental threat, even long after they are disposed of in specialized landfills, due to their complex composition and potential for leaching into waterways. This study focuses on the issue of elevated sulfate concentrations at the Martin Lake Steam Electric Station (MLSES) A-I Disposal Area in Panola County, Texas, where CCR are disposed of in a permanent landfill. Currently, this site is exceeding its regulatory limit of sulfate concentrations in its effluent and is in need of a cost-effective and sustainable solution to this problem. This research utilized benchtop experiments to investigate sulfate reducing …

Establishment Of Structure-Property-Processing Relationships For Design Of Sprayable Hydrogels And Amyloid/Peo Electrospun Composites, Xianjun Wang

Dissertations

The focus of this dissertation is the design, synthesis, characterization, and prototyping of bio-inspired materials to understand the role of structure, intermolecular interactions, and processing technique on the self-assembly, bioactive properties, and mechanical properties of the biomaterials. This work is divided into three research areas: 1) sprayable and adhesive glycopolymer based hydrogels; 2) decapeptide-based composite nanofiber mats; and 3) prototyping sutures and meshes via electrospinning. The established structure-property-processing relationships provide a foundation for designing biomaterials in the future.

The first chapter provides an introductory overview of the requirements necessary for the development of hydrogels, glycopolymers, and peptides, including relevant processing …

Biological Reinforcement Learning Simulation For Natural Enemy -Host Behavior: Exploring Deep Learning Algorithms For Population Dynamics, Komi Mensah Agboka, Emmanuel Peter, Erion Bwambale, Bonoukpoè Mawuko Sokame

All Peer-Reviewed Publications

This study introduces a simulation of biological reinforcement learning to explore the behavior of natural enemies in the presence of host pests, aiming to analyze the population dynamics between natural enemies and insect pests within an ecological context. The simulation leverages on Q-learning, a reinforcement learning algorithm, to model the decision-making processes of both parasitoids/predators and pests, thereby assessing the impact of varying parasitism and predation rates on pest population growth. Simulation parameters, such as episode count, duration in months, steps, learning rate, and discount factor, were set arbitrarily. Environmental and reward matrices, representing climatic conditions, crop availability, and the …

A Mathematical Model For Mapping The Insecticide Resistance Trend In The Anopheles Gambiae Mosquito Population Under Climate Variability In Africa, Komi Mensah Agboka, Mark Wamalwa, James Mutuku Mutunga, Henri E.Z. Tonnang

All Peer-Reviewed Publications

The control of arthropod disease vectors using chemical insecticides is vital in combating malaria, however the increasing insecticide resistance (IR) poses a challenge. Furthermore, climate variability affects mosquito population dynamics and subsequently IR propagation. We present a mathematical model to decipher the relationship between IR in Anopheles gambiae populations and climate variability. By adapting the susceptible-infected-resistant (SIR) framework and integrating temperature and rainfall data, our model examines the connection between mosquito dynamics, IR, and climate. Model validation using field data achieved 92% accuracy, and the sensitivity of model parameters on the transmission potential of IR was elucidated (e.g. μPRCC = …

Interactions Between Bacillus Thuringiensis And Selected Plant Extracts For Sustainable Management Of Phthorimaea Absoluta, Terry A. Ochieng, Komivi S. Akutse, Inusa J. Ajene, Dora C. Kilalo, Maina Muiru, Fathiya M. Khamis

All Peer-Reviewed Publications

Phthorimaea absoluta is a global constraint to tomato production and can cause up to 100% yield loss. Farmers heavily rely on synthetic pesticides to manage this pest. However, these pesticides are detrimental to human, animal, and environmental health. Therefore, exploring eco-friendly, sustainable Integrated Pest Management approaches, including biopesticides as potential alternatives, is of paramount importance. In this context, the present study (i) evaluated the efficacy of 10 Bacillus thuringiensis isolates, neem, garlic, and fenugreek; (ii) assessed the interactions between the most potent plant extracts and B. thuringiensis isolates, and (iii) evaluated the gut microbial diversity due to the treatments for …

Asthma Prevalence Among United States Population Insights From Nhanes Data Analysis, Sarya Swed, Bisher Sawaf, Feras Al-Obeidat, Wael Hafez, Amine Rakab, Hidar Alibrahim, Mohamad Nour Nasif, Baraa Alghalyini, Abdul Rehman Zia Zaidi, Lamees Alshareef, Fadel Alqatati, Fathima Zamrath Zahir, Ashraf I. Ahmed, Mulham Alom, Anas Sultan, Abdullah Almahmoud, Agyad Bakkour, Ivan Cherrez-Ojeda

All Works

Asthma is a prevalent respiratory condition that poses a substantial burden on public health in the United States. Understanding its prevalence and associated risk factors is vital for informed policymaking and public health interventions. This study aims to examine asthma prevalence and identify major risk factors in the U.S. population. Our study utilized NHANES data between 1999 and 2020 to investigate asthma prevalence and associated risk factors within the U.S. population. We analyzed a dataset of 64,222 participants, excluding those under 20 years old. We performed binary regression analysis to examine the relationship of demographic and health related covariates with …

Decoding Fgf/Fgfr Signaling: Insights Into Biological Functions And Disease Relevance, Oshadi Edirisinghe, Gaetane Ternier, Zeina Alraawi, Thallapuranam Krishnaswamy Suresh Kumar

Chemistry & Biochemistry Faculty Publications and Presentations

Fibroblast Growth Factors (FGFs) and their cognate receptors, FGFRs, play pivotal roles in a plethora of biological processes, including cell proliferation, differentiation, tissue repair, and metabolic homeostasis. This review provides a comprehensive overview of FGF-FGFR signaling pathways while highlighting their complex regulatory mechanisms and interconnections with other signaling networks. Further, we briefly discuss the FGFs involvement in developmental, metabolic, and housekeeping functions. By complementing current knowledge and emerging research, this review aims to enhance the understanding of FGF-FGFR-mediated signaling and its implications for health and disease, which will be crucial for therapeutic development against FGF-related pathological conditions.

Synergistic Anticancer Effect Of Pistacia Lentiscus Essential Oils And 5-Fluorouracil Co-Loaded Onto Biodegradable Nanofibers Against Melanoma And Breast Cancer, Obaydah Abd Alkader Alabrahim, Hassan Mohamed El Said Azzazy

Faculty Journal Articles

Chemoresistance and severe toxicities represent major drawbacks of chemotherapy. Natural extracts, including the essential oils of Pistacia lentiscus (PLEO), exhibit substantial anticancer and anti-inflammatory activities where different cancers are reported to dramatically recess following targeting with PLEO. PLEO has promising antimicrobial, anticancer, and anti-inflammatory properties. However, the therapeutic properties of PLEO are restricted by limited stability, bioavailability, and targeting ability. PLEO nanoformulation can maximize their physicochemical and therapeutic properties, overcoming their shortcomings. Hence, PLEO was extracted and its chemical composition was determined by GC–MS. PLEO and 5-Fluorouracil (5FU) were electrospun into poly-ε-caprolactone nanofibers (PCL-NFs), of 290.71 nm to 680.95 nm …

Long-Term Push–Pull Cropping System Shifts Soil And Maize-Root Microbiome Diversity Paving Way To Resilient Farming System, Abdul A. Jalloh, Fathiya Mbarak Khamis, Abdullahi Ahmed Yusuf, Sevgan Subramanian, Daniel Munyao Mutyambai

All Peer-Reviewed Publications

Background: The soil biota consists of a complex assembly of microbial communities and other organisms that vary significantly across farming systems, impacting soil health and plant productivity. Despite its importance, there has been limited exploration of how different cropping systems influence soil and plant root microbiomes. In this study, we investigated soil physicochemical properties, along with soil and maize-root microbiomes, in an agroecological cereal-legume companion cropping system known as push–pull technology (PPT). This system has been used in agriculture for over two decades for insect-pest management, soil health improvement, and weed control in sub-Saharan Africa. We compared the results with …

Deep Learning Approach For Accurate Segmentation Of Oil Spills In Marine Systems, Mohamed Elsheref

LSU New Orleans Theses and Dissertations

Oil spills present critical environmental hazards, threatening marine ecosystems and necessitating fast, accurate detection for effective mitigation. Synthetic Aperture Radar (SAR) imagery has been instrumental in detecting oil spills, but manual interpretation is often inefficient and prone to errors. This study addresses the limitations of manual methods by proposing a deep learning approach for automated oil spill detection and segmentation.

Utilizing a novel transfer learning-based semantic segmentation model, this research focuses on detecting oil slicks on the sea surface with higher accuracy and efficiency. The model leverages pre-trained networks and incorporates U-Net variants, including UNet++ and MultiResUNet, to optimize spatial …

Draft Final 2022 Insufficiently Reclaimed Sites Sampling Bres No. 37 – Josephine Shaft Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Artificial Intelligence And Machine Learning In Cancer Pain: A Systematic Review, Vivian Salama, Brandon Godinich, Yimin Geng, Laia Humbert-Vidan, Laura Maule, Kareem A Wahid, Mohamed A Naser, Renjie He, Abdallah S R Mohamed, Clifton D Fuller, Amy C Moreno

Faculty, Staff and Student Publications

Background/objectives: Pain is a challenging multifaceted symptom reported by most cancer patients. This systematic review aims to explore applications of artificial intelligence/machine learning (AI/ML) in predicting pain-related outcomes and pain management in cancer.

Methods: A comprehensive search of Ovid MEDLINE, EMBASE and Web of Science databases was conducted using terms: "Cancer," "Pain," "Pain Management," "Analgesics," "Artificial Intelligence," "Machine Learning," and "Neural Networks" published up to September 7, 2023. AI/ML models, their validation and performance were summarized. Quality assessment was conducted using PROBAST risk-of-bias andadherence to TRIPOD guidelines.

Results: Forty four studies from 2006 to 2023 were included. Nineteen studies used …

Learning To Represent Temporal Dynamics And Generative Factors For Intelligent Visual Navigation, Sahand Khoshdel

All Theses

Visual navigation systems are crucial in various applications, including autonomous driving, unmanned aerial systems (UAS), and industrial automation. For these systems to operate efficiently in dynamic environments, they must not only interpret complex surroundings but also anticipate changes over time. Temporal prediction—forecasting environmental changes like moving obstacles or shifting lighting conditions—enables navigation systems to act proactively, enhancing both safety and performance. This dissertation investigates representation learning methods both as a backbone feature extractor for RL agents as well as a proxy for systems oriented for Explainable AI (XAI). Two main projects are presented as case studies to achieve the aforementioned …

Informing Management Of American Shad (Alosa Sapidissima) In The Carolinas: Evaluating Novel Fish Passage Approaches And Acoustic Tracking Methods, Margaret Gaither

All Theses

Acoustic telemetry is a valuable tool for fisheries scientists to study the movements and migratory behaviors of aquatic organisms. A critical assumption of this method is that tagged fish exhibit similar behaviors and survival rates as their untagged counterparts. To investigate this, we conducted a 12-week laboratory study on adult American Shad (Alosa sapidissima) using gastroesophageal insertion of acoustic transmitters. We implanted 80 fish with dummy transmitters and monitored tag retention and survival. Our analysis, employing a mixed effects Cox’s proportional hazards model, revealed no significant differences in survival between tagged and control fish, regardless of sex. Additionally, …

Multiple Cut Systems Of Cannabis Sativa L. For Micropropagation Without The Use Of Cytokinins, Molly Mckay

All Theses

Micropropagation is a technique used to propagate clean, high-quality clonal stock plants using plant growth regulators (PGR) in a single harvest batch system. This two-part study uses an in vitro multiple harvest system “hedging” combined with the fed- batch media process, to observe (1) the effects of modified physical state and (2) LED light quality to improve shoot production and quality. In Experiment 1, four genotypes of Cannabis sativa (‘Cherry 1’,‘BaOx’,‘T1’,‘Peach’) were observed in three different physical states: stationary agar (A), stationary Oasis® infused with liquid (OIL_s) and agitated Oasis® infused with liquid (OIL_a). Fifteen …

Striking A Balance: Market Shock & Responses In Automotive Components Manufacturing, Emma Lane Mcgahey

All Theses

This thesis examines the effects of extreme market shocks on supply chain dynamics within the automotive industry. Through an analysis of demand data from an automotive manufacturer to its component suppliers (January 2018 to May 2024), the study investigates the relationship between market shocks and supply chain responses, providing insights into how auto components inventory management handles downstream responses to market shocks. With supporting public data—from FRED, BLS, and the U.S. Census Bureau resources—we explore two primary relationships: the impact of market shocks on the Average Standard Deviation of Demand (SDO) and the effect of demand variability on expedited pricing …