Digital Commons Network^™

Computational Investigation Of Energetic Materials: Influence Of Electronic And Steric Properties On Sensitivity And Decomposition Mechanisms, Elizabeth Ruth Zengel

Chemistry & Biochemistry Theses & Dissertations

Developing novel high energy density materials (HEDMs) requires knowledge of the causes and mechanisms of detonation. These chemical events are almost instantaneous and involve the release of a large amount of energy, which limits the experimental studies that can be performed on them. Computational methods including density functional theory (DFT) and molecular dynamics (MD) simulations have been used to investigate trigger bonds, those which break to initiate detonation. These bonds are commonly found within explosophores, substituents that increase the explosive potential of a molecule.

The Wiberg bond index (WBI) is an estimation of orbital overlap and bond strength between two …

Examples Of Mathematics Personified, Amenda N. Chow

Journal of Humanistic Mathematics

Synesthesia is a cognitive condition in which multiply senses are stimulated at once. There are different types of synesthesia. For example, in a documented study [9], a person with synesthesia when considering the number three associates it as a male and a jerk. This association is persistent, always the same and automatic. Presented here are a variety of examples about mathematics in personified form. These examples focus on using personification as a way to better understand and appreciate mathematics.

Memes As An Effective Approach To Increase Public Engagement With Mathematical Concepts, Juan M. Romero, Carlos Trenado

Journal of Humanistic Mathematics

A meme is a graphical concept or cultural item that is disseminated via the Internet, often through social media platforms. Memes serve as a mechanism for replicating cultural traits by incorporating aspects of cultural mutation and evolution. The potential of memes in learning and education has been emphasized in several recent studies. The present article examines the impact of memes in increasing public engagement with mathematics and mathematical concepts. By focusing on memes that exhibit specific attributes—such as emotional facial expressions of recognizable human characters and dialogues emphasizing the usefulness or beauty of a mathematical concept—we observe a significant increase …

Analyzing High-Risk Fertility Behavior For Sustainable Maternal-Child Health: A 2017 Sociodemographic Study In Urban And Rural Indonesia, Asti Annisa Utami, Fadhaa Aditya Kautsar Murti, Popy Yuniar, Milla Herdayati

Kesmas

Indonesia's goal of achieving Indonesia Emas 2045 hinges on improving Maternal-Child Health (MCH), essential for building a healthy and competitive population. Despite some advancements, the Maternal Mortality Rate (MMR) and Under-five Mortality Rate (U5MR) remain high, particularly because of High-Risk Fertility Behavior (HRFB). The HRFB poses significant risks to MCH, affecting both urban and rural women. This study aimed to identify the factors associated with HRFB in these areas to enhance MCH outcomes and support Indonesia's sustainable health goals. This cross-sectional study used a secondary dataset from the 2017 Indonesian Demographic Health Survey. A total of 20,530 women of reproductive …

Highly Contaminated Sediments From The Gowanus Canal (New York) Superfund Site: An Environmental Forensic Approach, Michael A. Kruge, Kevin K. Olsen, Eric A Stern, Maria Mastalerz, Albert Permanyer

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

The 2.5 km long Gowanus Canal (Brooklyn, NY, USA) is a severely contaminated urban waterway dating from the mid-19th century, listed as a US Environmental Protection Agency (USEPA) Superfund site since 2010. Applying an environmental forensics approach to the extensive USEPA data set, we detect systematic variations in parent PAH ring number distributions in the canal sediments, as well as an extraordinary enrichment in organic carbon. We subjected a supplemental sample set to a more detailed analysis by quantitative pyrolysis-GC-MS, Rock-Eval pyrolysis, and organic petrology. With these sensitive methods, we can confirm the alkyl-PAH fingerprint of coal tar (a legacy …

Tackling Data Quality Challenges In Remote Sensing: Solutions For Reliable Urban Heat Island Analysis, Wei Xia, Aqil Tariq, Hesham El-Askary, Rana Waqar Aslam, Elgar Barboza, Dmitry E. Kucher, Youssef M. Youssef, Habib Kraiem

Mathematics, Physics, and Computer Science Faculty Articles and Research

Urban heat islands (UHIs) pose critical challenges to public health, energy demand, and environmental sustainability, particularly in rapidly expanding urban regions. This study examines the complex relationship between building configurations and integrated green spaces, as well as their combined impact on thermal regulation. It focuses on addressing data quality issues commonly encountered in remote sensing applications. Using high-resolution multispectral and thermal imagery, we developed an integrated modeling approach that captures the collective influence of built form and green infrastructure on urban microclimates. A key finding is the significant linear inverse relationship between green space coverage and land surface temperature, underscoring …

The Effectiveness Of Remote Patient Monitoring In Reducing The Risk Of Rehospitalizations In Covid-19 Patients: A Meta-Analysis, Dela Riadi, Indang Trihandini, Dewi Nirmala Sari, Fikri Wijaya

Kesmas

An integrated analysis of various Remote Patient Monitoring (RPM) studies is needed to evaluate the reduction rate of the risk of rehospitalization in COVID-19 patients. This meta-analysis aimed to provide an overview of the effectiveness of RPM. A literature search through online databases (PubMed, Science Direct, Scopus, ProQuest, and Embase) was conducted from 2019 to 2022. After using the Cochrane Collaboration's risk of bias tool, five studies on COVID-19 were selected. Based on the data collected from 2,685 participants (intervention = 1,060, control = 1,625), the use of RPM was found to reduce rehospitalization by 0.56 times compared to not …

Cross-Cultural Adaptation And Validation Of Ranas-Based Instrument For Measuring Latrine Use Behavior In Indonesia, Vera Yulyani, Fatwa Sari Tetra Dewi, Iswanto Iswanto

Kesmas

Using toilets is a simple way to prevent diarrhea, yet no validated tool exists to measure this habit. This study aimed to develop and validate instruments for measuring latrine use consistency. This questionnaire was adapted from the risk, attitude, norm, ability, and self-regulation (RANAS) framework developed in India and modified for Indonesia. It was evaluated by three experts using the content validity index (CVI). The face validity index (FVI) was pilot-tested on 40 community respondents. Variables measured included behavior, habits, intentions to use toilets, knowledge, attitudes, norms, abilities, and self-regulation. Question items with relevance and clarity scores of item CVI …

Re: Comment Letter For Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Quality Assurance Project Plan Revision 01 (Dated June 6, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Assessing Effectiveness Of Runnel Restoration In New England Salt Marsh Habitats, David M. Burdick, Grant Mckown, Gregg Moore, Jenny Gibson, Wenley Ferguson, John Herbert, Nancy Pau, Susan Adamowicz, Geoff Wilson

Faculty Publications

Rising sea levels that increase flooding in salt marshes recovering from hydrologic impairments is reducing nesting habitat for salt marsh sparrows. Abandonment of colonial farming practices (1600s through 1900s) has resulted in large, waterlogged basins characterized by shallow depressions (pannes) dominated by short-form Spartina alterniflora and unvegetated megapools that are subsiding. A relatively new technique designed to provide regular tidal flooding and drainage to the waterlogged basins that have formed on the marsh is runnelling – creation of shallow hydrologic features on the marsh surface. Will runnels result in revegetation of pannes and pools with productive perennial grasses that are …

Revised Draft Final Uniform Federal Policyquality Assurance Project Plan, Hydrogeologic, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Green Innovation: Optimizing The Potential Of Plastic Waste As An Alternative To Fossil Fuels, Hani Alfiyani, Evi Gusmayanti, Nelly Wahyuni

Journal of Environmental Science and Sustainable Development

Plastic bag waste has the potential to be converted into alternative fuel oil through the pyrolysis method. This study applies the principle of thermal pyrolysis, conducted without oxygen, at the Edelweis Integrated Waste Management Site. The purpose is to analyze the characteristics of fuel oil derived from plastic bag waste based on parameters such as density, viscosity, calorific value, and acid number, as well as to estimate the potential fuel oil yield from plastic bag waste in Pontianak City. The results show that the density, viscosity, and calorific value of the produced fuel oil meet or closely approach standard requirements. …

Social Trends Emerging In A Mexican Village Community Involved In A Leaf Nutrient Supplementation Project Offered As Nutritional Intervention Scheme, T M. Ostrowski-Meissner, H T. Ostrowski-Meissner

IGC Proceedings (1977-2023)

Social analysis of the leaf nutrient supplementation (LNS) project using protein concentrate from alfalfa in a Mexican village (Saltillo) has been made in an attempt to identify the social trends associated with the community's involvement with protein extraction from green vegetation as a nutritional intervention scheme. Through preliminary on site observation and review of available scheme records, emergent social trends were identified in:

1. the voluntary diversification of nutritional habits,

2. an extension of health services for the community, and

3. subtle change within the village social milieu. The suitability of the LNS project is discussed, and areas for further …

Effects Of Fluidized Bed Combustion Residue Application To Reclaimed Mine Land On Yield And Composition Of Forage And Performance Of Grazing Steers, K O. Smedley, J P. Fontenot, V G. Allen, H D. Perry, O L. Bennett

IGC Proceedings (1977-2023)

Fluidized bed combustion residue (FBCR), a waste product resulting from the addition of limestone to coal prior to combustion, is high in sulfur (S) and has approximately 50% of the neutralizing capacity of limestone. Research was conducted to study effects of repeated applications of FBCR to pastures on forage yield and composition, and on performance and health of grazing cattle. Three treatments were applied in three replicated .81 ha pastures located on acidic reclaimed land which had been previously mined by mountain top removal. Treatments were control, dolomitic limestone (3380 kg/ha) and FBCR (6760 kg/ha), applied in split applications. Pastures …

Learning From Conditional Data Distributions, Jizhou Huang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Traditional machine learning paradigms often rely on a single global model trained on an entire dataset, aiming for broad generalization across all instances. However, in many real-world applications, the underlying data distribution is heterogeneous, and meaningful predictions often require models that focus on specific subpopulations rather than treating the data as a whole. This motivates the study of learning from conditional distributions, a framework where predictive models are designed to capture the structure and properties of restricted subsets of the data, leading to improved accuracy, fairness, and interpretability. This dissertation explores three key subproblems that exemplify different aspects of learning …

Analysis Of The Impact And Adaptation Of Tidal Floods From Coastal Landscape Area Communities In Poasia District, Kendari City, Indonesia, La Ode Hadini, La Aba, Noor Husna Khairisa, Nikita Jasmine Almira

Jurnal Pendidikan Geografi: Kajian, Teori, dan Praktek dalam Bidang Pendidikan dan Ilmu Geografi

Poasia District is located in the coastal area of the southern part of Kendari City, which is highly susceptible to tidal flooding. However, the extent of the community's exposure to these events and their subsequent adaptation measures remain to be fully delineated. This study examines the impacts of tidal flooding and the adaptation patterns of the Poasia Coastal Community to the tidal flood disaster. This research employed a descriptive qualitative method, which was carried out through document review, interviews involving 34 respondents, and field observations. The results of this study indicate that tidal flooding exerts a negative impact on the …

Multiclass Cyberbullying Detection Using Advanced Neural Network Architectures: A Comparative Study Amidst The Covid-19 Pandemic, Mahyar Alinejad

Data Science and Data Mining

Amidst the COVID-19 pandemic, the digital communication landscape has seen an unprecedented rise in cyberbullying incidents. Addressing this critical issue, our study develops and evaluates a novel multiclass cyberbullying detection framework employing several advanced neural network architectures—namely Neural Networks (NN), Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Gated Recurrent Units (GRU). Utilizing a balanced dataset created through Dynamic Query Expansion, this research benchmarks the performance of these models in accurately classifying cyberbullying according to specific victim attributes such as age, ethnicity, gender, and religion. Our results demonstrate that LSTM and GRU models, in particular, exhibit superior performance …

Multiclass Cyberbullying Detection Using Advanced Neural Network Architectures: A Comparative Study Amidst The Covid-19 Pandemic, Mahyar Alinejad

Data Science and Data Mining

Amidst the COVID-19 pandemic, the digital communication landscape has seen an unprecedented rise in cyberbullying incidents. Addressing this critical issue, our study develops and evaluates a novel multiclass cyberbullying detection framework employing several advanced neural network architectures—namely Neural Networks (NN), Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Gated Recurrent Units (GRU). Utilizing a balanced dataset created through Dynamic Query Expansion, this research benchmarks the performance of these models in accurately classifying cyberbullying according to specific victim attributes such as age, ethnicity, gender, and religion. Our results demonstrate that LSTM and GRU models, in particular, exhibit superior performance …

Computational And In Vitro Investigation Of P. Crocatum Bioactive Compounds As Pancreatic Lipase Inhibitors, Gusnia Meilin Gholam, Dimas Andrianto, Dewi Anggraini Septaningsih, Mega Safithri

Karbala International Journal of Modern Science

Obesity, a prevalent metabolic disorder characterized by excessive fat accumulation, can severely affect overall health if left untreated. This study investigated the potential of a 70% ethanol extract from Piper crocatum (red betel) leaves as an in vitro inhibitor of pancreatic lipase (PL), supported by computational analyses to identify alternative compounds to orlistat. The phytochemical profile was characterized using LC-MS/MS, revealing alkaloids and terpenoids with contents of 1.1 ± 0.01 mg CE/g and 3.14 ± 0.3 mg UAE/g, respectively. The extract exhibited 49 ± 9.1% inhibition of PL activity. Molecular docking identified three promising compounds: calanolide A (10.43 kcal/mol), myricanone …

In Silico Prediction Of Cytotoxic T-Cell Epitopes From Helicobacter Pylori Virulence Factors Using An Immunoinformatics Approach, Demy Valerie Chacon, Kiana Alika Co, Daphne Noreen Enriquez, Aubrey Love Labarda, Reanne Eden Manongsong, Edward Kevin B. Bragais

Biology Faculty Publications

Background: Helicobacter pylori infects approximately half of the global population, leading to gastric and duodenal ulcers. Despite the availability of antibiotics, challenges such as patient reluctance, high treatment costs, and antibiotic resistance limit their effectiveness, making vaccination a promising alternative. This study used immunoinformatics to identify candidate epitopes for a multiepitope vaccine construct against H. pylori.

Material and methods: The protein variability server was utilized for conservation analysis. The epitopes were screened for antigenicity, allergenicity, toxicity, cross-reactivity, and population coverage. Selected epitopes were docked with their corresponding human leukocyte antigen (HLA) alleles, and thermodynamic quantities were determined. Five virulence …

Comparative Study Of Machine Learning Models For Predicting The Market Value Of Professional Football Players, Álvaro Salvador López

Master's Theses or Doctor of Nursing Practice

The market value of professional football players is a critical factor in decision-making for clubs, agents, and analysts. Accurate player valuation impacts transfers, contract negotiations, and financial planning. In recent years, data-driven approaches have emerged to support traditional scouting with predictive analytics. This thesis presents a comparative study of machine learning models to estimate the market value of football players based on historical performance and personal attributes.

This thesis presents a comparative study of two independently developed machine learning systems designed to predict the market value of football players for the 2020–2021 season. Both systems were trained using real data …

Derivation Of Adjoint Based Error Estimates For Nonlinear Ordinary Differential Equations With Application To Multistage Sir Models With Demographics, Daniel Alcala

Mathematics & Statistics ETDs

Ordinary Differential Equations (ODEs) are central to the mathematical modeling of various real-world phenomena, from mechanical systems governed by Newton’s laws to epidemic dynamics described by SIR-type ODEs. Since many ODEs do not admit closed-form analytic solutions, we approximate them numerically (e.g., with Euler’s, Runge–Kutta, or other such methods). This raises the key question: How accurate are these numerical solutions? In particular, reliably estimating the error in some quantity of interest (QoI) at time T without having an exact solution is of great scientific interest.

The first main contribution of this thesis is the development and analysis of adjoint-based error …

A Data-Driven Approach To Time Series Forecasting And Clustering Of U.S. Regional Drug Overdose Mortality, Koshali Hamy Muthunama Gonnage

Mathematics & Statistics ETDs

The increasing rate of drug overdose deaths in the United States poses a critical public health challenge, particularly due to the surge in synthetic opioids and other high-risk substances. This study presents a data-driven framework that integrates time series forecasting and clustering techniques. Monthly mortality data for five key drug types: cocaine, fentanyl, heroin, methamphetamine, and oxycodone were analyzed using four time series forecasting models: ARIMA, ETS, TBATS, and NNAR. These models were evaluated using standard accuracy metrics RMSE, MAPE, and MAE to assess predictive performance. Signal decomposition approach based on Singular Value Decomposition and subspace modeling was employed to …

Using Triple Oxygen Isotopes To Investigate Water Usage In Desert Ecosystems, Cloe V. Knutson

Earth and Planetary Sciences ETDs

In arid environments, maintaining water balance can be more critical for survival than obtaining food. As droughts intensify, understanding how animals manage body water is essential. Triple oxygen isotope analysis provides a novel way to trace water sources in animals, distinguishing contributions from free water, food-derived oxygen, and atmospheric O₂. We developed an equilibration method using CO₂–H₂O oxygen exchange and measured δ^’18O and Δ^’17O values via tunable infrared laser direct spectroscopy (TILDAS). Validated against traditional fluorination methods, this technique enables streamlined analysis of whole blood and plant samples. Applied to …

A Mutational Analysis Of Thatisin: How Single Point Mutations Impact The Biosynthetic Process Of A Group 16 Graspetide, John F. Boynton Jr

Chemistry and Chemical Biology ETDs

Abstract:

Graspetides are a family of Ribosomally synthesized and Post-translationally modified Peptide (RiPP) natural products named for their ATP Grasp Macrocyclases. We identified several Graspetide Biosynthetic Gene Clusters containing common double glycine cleavage motifs and attempted characterization of the mature Graspetides. One of the resulting peptides, Thatisin, has a topology with two interlocking macrolactones installed by a single ATP Grasp Ligase named ThtC. Here we use single and double point mutations to observe the impact or variation on the installation of these macrocycles. Alanine scan mutagenesis is used to assess leader peptide residues in the precursor peptide ThtA to determine …

Network Intelligence For Next-Generation Wireless Networks: Advancing Distribution And Coordination, Yonatan Melese Worku

Electrical and Computer Engineering ETDs

Next-generation wireless networks, encompassing 6G and beyond, face rigorous demands for ultra-low latency, ubiquitous connectivity, exceptionally high data rates, and robust security, necessitating innovative approaches to resource optimization and network protection. This dissertation proposes a pioneering framework that synergizes advanced methodologies—deep reinforcement learning, deep learning, blockchain, and multi-agent systems—to address these challenges. Distributed architectures, underpinned by AI-driven multi-agent systems, form the backbone of this framework, enabling seamless integration and intelligent orchestration across diverse domains. The research advances IoT-based systems leveraging machine learning for resource efficiency in healthcare applications, develops reinforcement learning-driven frameworks to optimize energy and coverage for Unmanned Aerial …

Table Of Contents

Journal of the South Carolina Academy of Science

No abstract provided.

07.28.2025 Ored Connect, Liz Williamson

ORED Newsletter

On-demand training courses released

• Mentoring
• My Project Was Funded, Now What?

Notice of Funding Opportunity SMART Act Accelerate Initiative

Memo Regarding Contact from Federal Agencies

Urban Landscape Recovery And Lulc Analysis: A Deep Learning Approach To Post-Extreme Rainfall Impacts In Dubai, Xin Hong

All Works

From April 14 to 18, 2024, the United Arab Emirates (UAE) experienced its heaviest rainfall in 75 years, resulting in widespread flooding across multiple emirates, including Dubai. This study utilizes high-resolution PlanetScope imagery and a U-Net deep learning model to assess the flood impact and analyze post-rainfall recovery patterns in Dubai’s urban landscape. By integrating Sentinel-2derived land use and land cover (LULC) data to refine the training dataset, a high-accuracy U-Net model was developed through transfer learning that effectively classified pre- and post-rainfall LULC. Post-rainfall LULC change detections indicate that 23.8 km² of land was flooded, which is equivalent …

Secure Frameworks For User Motion Data In Virtual Reality, Jayasri Sai Nikitha Guthula

Theses and Dissertations

Virtual Reality is an innovative technology transforming industries such as gaming, healthcare, and remote collaboration. The increasing deployment of these systems results in the continuous collection of telemetry data, including motion patterns, hand gestures, and spatial interactions. This data is valuable for enhancing user experiences and optimizing system performance. However, it also introduces significant privacy risks. Unlike traditional digital footprints, motion data captures fine-grained physical behaviors that can be linked to individual users, making anonymization ineffective in preventing re-identification.This research introduces secure frameworks for user motion data in virtual reality, each proposed framework addressing privacy preservation from a different angle. …