Digital Commons Network^™

Transient Diode Laser Absorption Spectroscopy For Measuring Collisional Quenching Rates Of Co And Its Potential For Studying H2o, Jordan M. Polvere

Master’s Theses

Motivated by the necessity of non-LTE models that account for species that are not in Local Thermodynamic Equilibrium (LTE) in Titan’s and Earth’s atmospheres, collisional quenching rates of CO and H2O_(g) have been studied. Providing more accurate and precise values of collisional quenching rate coefficients is crucial in the development of more advanced atmospheric models, which are important to fields of science such as meteorology and astronomy. Rates of collisional quenching of CO(v=1,2) by CO and CO(v=2) by N₂ at approximately 301-321 K were measured by transient diode laser absorption spectroscopy. The rate coefficients of CO(v=1)-CO, CO(v=2)-CO, and …

Pitching The Use Of Squared And Interaction Terms In Regression Via Baseball Heat Maps, Lucas Chepelsky

Williams Honors College, Honors Research Projects

This project will examine the impact of using second-order terms in regression. For illustration, we use an example of regression where a baseball player's three by three heat map, including the height and distance from inside to outside of the pitch, are variables used to predict batting average. We find that second-order terms are crucial in discovering nonlinear relationships and interaction effects in regression models, and maintain that the common practice of using first-order additive models is insufficient.

Machine Learning-Based Analysis Of Dna Methylation Patterns In E.Lenta, Tsion Tsegaye Sherbeza

All Graduate Theses, Dissertations, and Other Capstone Projects

Methylation patterns in bacterial genomes, such as those found in Eggerthella lenta, take roles in mediating microbial interactions with their environment, host, and external stressors. These patterns are formed by DNA methylation with diverse sequence specificities that provide insights into the DNA sequence regulation and defense against bacteriophages. We utilize computational approaches and machine learning models to identify and analyze 5mC and 6mA methylation motifs in E. lenta genomes. By integrating host characteristics such as age, birth country, gender, and medication history, we explore 1) the predictive relationships between 5mC & 6mA methylation types in E. lenta strains and …

“Zero” Porosity High Loading Nmc622 Positive Electrodes For Li-Ion Batteries, Haidar Y. Alolaywi, Kubra Uzun, Yang-Tse Cheng

Chemical and Materials Engineering Faculty Publications

LiNi0.6 Mn0.2Co0.2 O 2 (NMC622) is a widely used positive electrode material for lithium-ion batteries, including electric vehicles. In this work, we investigated the effects of porosity, ranging from “zero” to the typical 35%, on the electrochemical behavior of high- loading NMC622 electrodes. Although it is well known that the energy density of the electrode increases with increasing areal capacity and decreasing porosity, NMC-positive electrodes with exceedingly low porosity (e.g., near zero) and high loading (e.g., 4 mAh cm−2 ) have not been investigated. Here, we report an intriguing observation that the “zero porosity” NMC electrode can have higher capacity …

The Educational Affordances And Challenges Of Chatgpt: State Of The Field, Helen Crompton, Diane Burke

STEMPS Faculty Publications

ChatGPT was released to the public in November 30, 2022. This study examines how ChatGPT can be used by educators and students to promote learning and what are the challenges and limitations. This study is unique in providing one of the first systematic reviews using peer review studies to provide an early examination of the field. Using PRISMA principles, 44 articles were selected for review. Grounded coding was then used to reveal trends in the data. The findings show that educators can use ChatGPT for teaching support, task automation, and professional development. These were further delineated further by axial sub …

Impacts To Anxiety, Depression, And Psycho-Spiritual Metrics After Ketamine-Assisted Psychotherapy In Palliative Care Patients At The Aims Institute, Thomas Luedeke

Doctor of Nursing Practice Projects

There is considerable evidence that palliative care patients disproportionately experience anxiety, depression, and existential distress related to their chronic illnesses. Additionally, conventional therapies tend to be less effective in the treatment of this patient population. As such, research is being conducted into novel therapies. One of the promising therapies currently under active investigation is ketamine-assisted psychotherapy (KAP) which involves a combination of the administration of the dissociative anesthetic ketamine combined with psychotherapy.

Two clinical trials are being conducted at the Advanced Integrative Medical Sciences (AIMS) Institute in Seattle, WA, the purposes of which are to evaluate integrative care for patients …

Greenwood Library Report 2022-2024, Greenwood Library

Library Annual Reports and Strategic Plans

No abstract provided.

Relationship Between Socking Rate And Production Of Stocker Hybrid Tilapia And Water Quality In A Mixtotrophic Biofloc System, Bartholomew W. Green, Steven D. Rawles, Candis L. Ray, Matthew E. Mcentire

United States Department of Agriculture-Agricultural Research Service / University of Nebraska-Lincoln: Faculty Publications

Intensified production of stocker-size tilapia can be accomplished using the biofloc technology production system. Stocker-size tilapia (ca. 10–200 g/fish) are raised for subsequent stocking for grow-out to market size. The relationship between stocking rate and the production of stocker-size hybrid tilapia (Oreochromis aureus x O. niloticus) was evaluated in two studies in outdoor mixotrophic biofloc tanks. Hybrid tilapia were stocked in 18.6-m² (15.7-m³) tanks at 50–150 fish/m² (59–178 fish/m³) in 25 fish/m² (30 fish/m³) increments in Study 1 and grown for 141–143 days. Stocking rates evaluated in 4.7-m …

A Generative Approach For Document Enhancement With Small Unpaired Data, Mohammad Shahab Uddin, Wael Khallouli, Andres Sousa-Poza, Samuel Kovacic, Jiang Li

Engineering Management & Systems Engineering Faculty Publications

Shipbuilding drawings, crafted manually before the digital era, are vital for historical reference and technical insight. However, their digital versions, stored as scanned PDFs, often contain significant noise, making them unsuitable for use in modern CAD software like AutoCAD. Traditional denoising techniques struggle with the diverse and intense noise found in these documents, which also does not adhere to standard noise models. In this paper, we propose an innovative generative approach tailored for document enhancement, particularly focusing on shipbuilding drawings. For a small, unpaired dataset of clean and noisy shipbuilding drawing documents, we first learn to generate the noise in …

Prevalence Of Resistant Escherichia Coli Isolated From Local Meats Sold In Tema Metropolis, Ghana, Frederick Adzitey, Innocent Allan Anachinaba, Charles Addo-Quaye Brown, Nurul Huda, Masmuniri Rambli

ASEAN Journal on Science and Technology for Development

Contamination of meat by Escherichia coli (E. coli) can take its source from the live animal or by cross contamination. The study determined the prevalence of resistance of E. coli isolated from locally produced meats in the Tema Metropolis. Beef (n=200), chicken (n=200) and pork (n=200) were randomly selected and evaluated for the presence of E. coli using the procedure in the Bacteriological Analytical Manual of USA-FDA. The disc diffusion method was used for antibiotic susceptibility test of E. coli (n=55) isolates. Locally produced beef (67%), chicken (41%) and pork (23%) were contaminated by E. coli. Escherichia coli isolates were …

Borate-Based Bioactive Glasses Properties: Clinical And Biomedical Applications, Sarah Fakher, David J. Westenberg

Biological Sciences Faculty Research & Creative Works

Borate bioactive glasses (BBGs) constitute the recently produced bioactive glasses (BGs) in the domain of bioactive materials, offering enhanced functionalities over conventional silicate and phosphate BGs. This advancement is primarily characterized by BBGs' rapid yet controllable degradation rates, superior bioactivity, and the ability to swiftly form a hydroxyapatite layer (HAP) upon interaction with physiological fluids. A distinguishing feature of BBGs lies in their customizability; doping with therapeutic metal ions tailors their bioactivity towards specific physiological responses, including promoting angiogenesis, antibacterial activity, and osteogenesis. This versatility of BBGs' applications extends to bone regeneration, wound healing, drug delivery systems, and potentially nerve …

Investigating Ammonium Toxicity In The Performance Of Recirculating Periphytic Algal Wastewater Treatment Systems, Oluchuku Richie Ochonogor

Theses and Dissertations

Freshwater nutrient enrichment from wastewater facilities and other sources can lead to freshwater eutrophication, a threat to global aquatic ecosystems. Mechanical and chemical ways to curb this threat are either too expensive or not sustainable, and thus, not feasible. Compared to mechanical and other methods, sustainable, inexpensive biological methods (for example, algal treatment systems) have therefore been developed for the removal of excess nutrients from wastewater. By design, secondary waste treatment facilities (WWTF) remove organics and solids and lower oxygen demanding substances; however, they may not remove enough nutrients to protect freshwater ecosystems in all cases. While algae-based biological methods …

School-Based Educators’ Perceptions Of Professional Development And Its Impact On Their Ability To Improve Literacy Instruction For Underperforming K-2 Students, Monica Mcdaniel

Theses and Dissertations

The purpose of this qualitative exploratory case study was to examine school-based educators’ perceptions of professional learning and its impact on their ability to improve literacy instruction. The perceived role of the principal in the implementation, monitoring, and sustaining professional learning was also explored. A total of eight teachers, two media specialists, two instructional coaches, and five school leaders at two elementary schools in the Southeast United States participated in the study. Findings include the importance of quality, ongoing professional development, the leader’s role in planning, participation in, and supporting teachers through the professional development process, and everyone’s role in …

A Phytochemical Analysis Of Secondary Metabolites In Eupatorium Serotinum, Elise Snow

Theses and Dissertations

Phytochemistry, a subset of Natural Products Chemistry, studies chemically derived products from natural substances. Advances in this field have important applications in medicinal research due to the distinctive and unique properties of natural compounds. All metabolites are produced from the metabolic cycle, which is a pathway that provides energy for the organism. These metabolic compounds vary greatly and are classified based on their function within the organism. Primary metabolites are abundant and contribute to organism growth, development, and maintenance of energy. Secondary metabolites are found in lesser quantity and correlate to natural defense mechanisms. For example, salicylic acid is a …

K-12 Teacher Perceptions Of Online Learning And Information Technology Support Post Covid-19 Pandemic, Michael Wayne Carraway Ii

Theses and Dissertations

This study examines K-12 teacher technology acceptance through their perceptions of the learning management system Google Classroom, in the aftermath of the COVID-19 pandemic. This correlational research study is conducted through a survey adapted from the Technology Acceptance Model, Information technology support analysis, and a functionality usability survey. This study examines the relationships between functionality, usability, IT support, perceived usefulness (PU), perceived ease of use (PEOU), attitudes towards use (ATU), behavioral intention to use (BI), and actual usage (AU). Structural equation modelling is conducted at the construct level in order to determine relationships between constructs. Additionally, this study explores assessment …

The Effect Of Transformational Leadership On Teacher Burnout: A Sequential Explanatory Mixed Methods Study, Jessica Grace Watson

Theses and Dissertations

The teaching field is a depleting workforce and more teachers are experiencing burnout, which is causing them to leave the profession (Marken & Agrawal, 2022; Nguyen et al., 2022). However, transformational leadership can improve job satisfaction, which can potentially reduce teacher burnout (Barnett et al., 2001; Erkutlu, 2008; Tian et al., 2021). The purpose of this study, grounded in Bass’ (1985) transformational leadership framework, was to examine the effect of transformational leadership on teacher burnout and to analyze the teachers’ perceptions of transformational leadership support. The study answered the following research questions: What is the relationship between transformational leadership and …

Teacher Perceptions Of A Literacy Intervention Implementation In Middle School: A Case Study, James E. Maye Jr.

Theses and Dissertations

The purpose of this qualitative case study was to explore the perspectives of teachers at Oakridge Middle School regarding the implementation of a literacy intervention and evaluate its impact on students’ literacy achievement. The study was guided by the social learning theory, which posits that a literacy intervention program would enhance students’ literacy skills. The study findings indicated that the program improved students’ reading and writing confidence and comprehension abilities. The successful implementation of the literacy intervention was facilitated by teachers’ collaboration and the use of data trackers, despite challenges, such as student buy-in and motivation issues. Technology-based programs, such …

Multiple Imputation For Robust Cluster Analysis To Address Missingness In Medical Data, Arnold Harder, Gayla R. Olbricht, Godwin Ekuma, Daniel B. Hier, Tayo Obafemi-Ajayi

Mathematics and Statistics Faculty Research & Creative Works

Cluster Analysis Has Been Applied To A Wide Range Of Problems As An Exploratory Tool To Enhance Knowledge Discovery. Clustering Aids Disease Subtyping, I.e. Identifying Homogeneous Patient Subgroups, In Medical Data. Missing Data Is A Common Problem In Medical Research And Could Bias Clustering Results If Not Properly Handled. Yet, Multiple Imputation Has Been Under-Utilized To Address Missingness, When Clustering Medical Data. Its Limited Integration In Clustering Of Medical Data, Despite The Known Advantages And Benefits Of Multiple Imputation, Could Be Attributed To Many Factors. This Includes Methodological Complexity, Difficulties In Pooling Results To Obtain A Consensus Clustering, Uncertainty Regarding …

Datafication, Power, And Publics In India's National Digital Health Ecosystem, Ramya Chandrasekhar

Socio-Legal Review

While evident for a long time, the COVID-19 pandemic starkly illustrated the need to strengthen India’s public healthcare system. But since 2017, the solution to India’s public health woes takes the shape of the National Digital Health Ecosystem (‘NDHE’) – a digital system for the generation, use, and “frictionless” circulation of health data across healthcare actors through the use of artefacts such as health IDs, electronic health records, data standards, and federated computing architectures. These artefacts are not neutral technological systems. Rather, together with social practices, they constitute a “data infrastructure.” Seeing the NDHE as a data infrastructure allows us …

Full Issue, Socio-Legal Review

Socio-Legal Review

No abstract provided.

Accelerating L-Shaped Two-Stage Stochastic Scuc With Learning Integrated Benders Decomposition, Fouad Hasan, Amin Kargarian

Faculty Publications

Benders decomposition is widely used to solve large mixed-integer problems. This article takes advantage of machine learning and proposes a variant of Benders decomposition to tackle two-stage stochastic security-constrained unit commitment (SCUC). The problem is decomposed into a master problem (MP) and subproblems (SPs) corresponding to individual load scenarios. The primary objective is to mitigate computational expenses and memory consumption associated with Benders decomposition by generating tighter cuts and reducing the MP's dimensions. A regressor reads load profile scenarios and predicts objective function proxy values for the SPs, enabling the creation of tighter cuts for the MP. The numerical difference …

Performance Optimization Of Software-Defined Industrial Internet-Of-Things (Sd-Iiot), Jehad Ali, Celestine Iwendi, Gaoyang Shan, Hsiao Chun Wu, Mohammed J.F. Alenazi, Zaid Bin Faheem, Cresantus N. Biamba

Faculty Publications

Software-Defined Networking (SDN) offers a centralized network management approach that can effectively address the complex and varied traffic demands characteristic of Industrial Internet of Things (IIoT) environments by decoupling the control plane from the data plane. The centralized control architecture of SDN necessitates the performance optimization of controllers to manage diverse traffic efficiently within IIoT applications. This paper explores the criteria for selecting controllers in SDN-enabled IIoT (SD-IIoT) environments, utilizing the Less Complex Analytic Network Process (LC-ANP) to establish their prioritization. A ranking system for SD-IIoT controllers is formulated using LC-ANP, and experimental validation of this method underscores its effectiveness …

Tensor Z -Transform, Shih Yu Chang, Hsiao Chun Wu

Faculty Publications

The multi-input multioutput (MIMO) systems involving multirelational signals generated from distributed sources have been emerging as the most generalized model in practice. The existing work for characterizing such a MIMO system is to build a corresponding transform tensor, each of whose entries turns out to be the individual z-transform of a discrete-time impulse response sequence. However, when a MIMO system has a global feedback mechanism, which also involves multirelational signals, the aforementioned individual z-transforms of the overall transfer tensor are quite difficult to formulate. Therefore, a new mathematical framework to govern both feedforward and feedback MIMO systems is in crucial …

A Machine Learning-Based Wrapper Method For Feature Selection, Damodar Patel, Amit Saxena, John Wang

Department of Information Management and Business Analytics Faculty Scholarship and Creative Works

This paper presents a two-stage feature selection scheme using machine learning techniques. In the first stage a wrapper method is adopted to select various combinations of subsets of features from the original dataset. The performance of the model is evaluated by three classifiers: K-Nearest Neighbor (KNN), Support Vector Machines (SVM), and Random Forest (RF). In the second and final stage, a sequential backward feature selection Method is applied. The proposed method is demonstrated on eighteen datasets and the average classification accuracy of eighteen datasets achieved is 89.81%, 87.55%, and 89.82% using the KNN, SVM, and RF classifiers, respectively with a …

Analyzing The Complexity Of Us Federal Debt: A Mathematical Approach, John Wang, Arti Jain, Arun Kumar Yadav, Divakar Yadav

Department of Information Management and Business Analytics Faculty Scholarship and Creative Works

The United States federal debt has witnessed a significant surge over recent decades. This study delves into inquiries regarding the persistent patterns in federal debt, key factors driving this alarming trend, and the optimal timing for implementing corrective measures to mitigate its speeding flight. Utilizing modern machine learning techniques, notably Random Forest (RF) and Support Vector Regression (SVR), alongside conventional statistical forecasting techniques, the research aims to predict future trends. It emphasizes the critical role of business analytic thinking in deciphering fiscal system-based complexities. To address the mounting challenges, these research findings underscore the urgent necessity for efficacious policies to …

A Case Study On Variations In Network Structure And Cross- Sector Alignment In Two Local Systems Serving Pregnant And Parenting Women In Recovery, Liza M. Creel, Yana Feygin, Madeline Shipley, Deborah Winders Davis, Tiffany Cole Hall, Chaly Downs, Stephanie Hoskins, Natalie Pasquenza, Scott D. Duncan

Biostatistics Faculty Publications

Objective: To describe network structure and alignment across organizations in healthcare, public health, and social services sectors that serve pregnant and parenting women with substance use disorder (SUD) in an urban and a rural community.

Data Sources and Study Settings: Two community networks, one urban and one rural with each including a residential substance use treatment program, in Kentucky during 2021.

Study Design: Social network analysis measured system collaboration and cross-sector alignment between healthcare, public health, and social services organizations, applying the Framework for Aligning Sectors. To understand the alignment and structure of each network, we measured network density overall …

Higher First 30-Day Dose Of Buprenorphine For Opioid Use Disorder Treatment Is Associated With Decreased Mortality, Feitong Lei, Michelle R. Lofwall, Jana Mcanich, Reuben Adatorwovor, Emily Slade, Patricia R. Freeman, Daniela Moga, Nabarun Dasgupta, Sharon L. Walsh, Rachel Vickers-Smith, Svetla Slavova

Biostatistics Faculty Publications

Objective: Buprenorphine is a medication for opioid use disorder that reduces mortality. This study aims to investigate the less well-understood relationship between the dose in the early stages of treatment and the subsequent risk of death.

Methods: We used Kentucky prescription monitoring data to identify adult Kentucky residents initiating transmucosal buprenorphine medication for opioid use disorder (January 2017 to November 2019). Average daily buprenorphine dose for days covered in the first 30 days of treatment was categorized as ≤8 mg, >8 to ≤16 mg, and >16 mg. Patients were followed for 365 days after the first 30 days of buprenorphine …

Fractal Surface Recovery And Self-Healing Contributed To Sustainable Superhydrophobicity: A Review, Yunfei Peng, Zhihang Ma, Xiao Wang, Junru Li, Xinlin Li, Chuanwei Zhang, Tian He, Guoqiang Li, Pengfei Zhang

Faculty Publications

The concept of superhydrophobicity has been widely used after years of theoretical and experimental exploration. Researchers have obtained materials with excellent surface superhydrophobicity for numerous areas (e.g. textiles, paints, and coatings industries), through different design and synthesis methods using low surface energy components (LSECs) and micro/nanohierarchy composite structures. However, the durability of superhydrophobic material surfaces has gradually become a prominent obstacle to restricting applications. In this paper, advances in improving the durability of superhydrophobic surfaces in the past decade are reviewed, covering different schemes for recovering fractal surfaces based on the LSECs and micro/nanocomposite structures. It also presents a balanced …

Review Of Artificial Neural Networks For Wind Turbine Fatigue Prediction, Alshannaq, Aly Mousaad Aly

Faculty Publications

Wind turbines have emerged as a prominent renewable energy source globally. Efficient monitoring and detection methods are crucial to enhance their operational effectiveness, particularly in identifying fatigue-related issues. This review focuses on leveraging artificial neural networks (ANNs) for wind turbine monitoring and fatigue detection, aiming to provide a valuable reference for researchers in this domain and related areas. Employing various ANN techniques, including General Regression Neural Network (GRNN), Support Vector Machine (SVM), Cuckoo Search Neural Network (CSNN), Backpropagation Neural Network (BPNN), Particle Swarm Optimization Artificial Neural Network (PSO-ANN), Convolutional Neural Network (CNN), and nonlinear autoregressive networks with exogenous inputs (NARX), …

Slope Unit Maker (Sumak): An Efficient And Parameter-Free Algorithm For Delineating Slope Units To Improve Landslide Modeling, Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, Matthew M. Crawford

Faculty, Staff, and Affiliated Publications--KGS

Slope units are terrain partitions bounded by drainage and divide lines. In landslide modeling, including susceptibility modeling and event-specific modeling of landslide occurrence, slope units provide several advantages over gridded units, such as better capturing terrain geometry, improved incorporation of geospatial landslide-occurrence data in different formats (e.g., point and polygon), and better accommodating the varying data accuracy and precision in landslide inventories. However, the use of slope units in regional (> 100 km²) landslide studies remains limited due, in part, to the large computational costs and/or poor reproducibility with current delineation methods. We introduce a computationally efficient algorithm …