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A Nonlocal Lattice Particle Method For Modeling Hcp Polycrystalline Solids, Di Liu

University of Kentucky Doctoral Dissertations

Polycrystalline materials, composed of individual grains with varying grain size, shape, and crystallographic orientation are widely used in various engineering and industrial applications. Conventional applications of polycrystalline materials rely on the macroscopic performance, and the microstructural features are usually homogenized out. With the advancement of modern technologies and improvement of characterization methods, polycrystalline materials find their applications in meso- and micro-scale systems. At these length scales, the microscopic features including grain boundary characteristics significantly affect the material physical responses. As a result, the conventional continuum mechanics models become problematic, especially for material failure problems where the microstructural features play dominant …

Implementing The Lung Donor (Lundon) Acceptability Score In U.S. Donor Management And Transplant Decision-Making: A Multi-Aim, Mixed-Methods Protocol, Nikki E. Rossetti, Su-Hsin Chang, Yan Yan, Graham Jaensch-Frie, Charles R. Liu, Nahom Y. Seyoum, Meghna Katta, Arvind Kumar, Zhizhou Yang, Christian Oncken, Christy Hamilton, Kyle Stumbaugh, Brendan Heiden, Sarah Peskoe, Varun Puri, Et Al.

2020-Current year OA Pubs

BACKGROUND: Despite advances in transplantation science, a persistent shortage of donor lungs continues to limit access to life-saving lung transplants. The Lung Donor (LUNDON) Acceptability Score is a validated tool that predicts donor lung utilization and post-transplant recipient outcomes, but integration into practice remains limited. This study will evaluate determinants of LUNDON score adoption, its impact on clinical decision-making, and develop tools to support its implementation.

METHODS: This is a multi-aim mixed-methods pre-implementation study that will be conducted across U.S. Organ Procurement Organizations (OPOs) and lung transplant centers. Aim 1 will identify barriers and facilitators of LUNDON score adoption through …

On The Surface: The Mural Of Shireen Abu Akleh As Space For Encounter, Saja Abd El Hai

Dissertations and Theses @ UNI

No abstract provided.

Exploring Governance And Government Policies Of Preparedness And Response To Flooding In Juneau, Alaska, Derreck Asiamah

Dissertations and Theses @ UNI

No abstract provided.

Examining The Current And Potential Impacts Of Erosion, Flooding, And Permafrost Thaw On Small Businesses In The Lower Kuskokwim Basin, Alaska, Dela Yao Agbagba

Dissertations and Theses @ UNI

No abstract provided.

Stem Identities Of Iowa State University's Biological And Biomanufacturing Systems Technology Students, Levi Nettleton

Dissertations and Theses @ UNI

No abstract provided.

Temporal Analysis Of Supraglacial Drainage Systems On The Greenland Ice Sheet From 2009-2017 Using Very High-Resolution Satellite Imagery, Field Measurements, And Climate Models, Natalie Gallegos Nunez

Dissertations and Theses @ UNI

No abstract provided.

Edge Guided Channel Attention In Fsrcnn: A Novel Approach For Depth Super Resolution, Yagneshkumar Jayantilal Parmar, Paresh M. Dholakia

Mansoura Engineering Journal

Depth images from low-cost sensors often suffer from blurred edges and structural distortions when processed with standard super-resolution models. While FSRCNN is efficient for RGB images, it struggles to handle the unique geometric requirements of depth maps. To solve this, we propose the Edge Guided Channel Attention FSRCNN (EGCA FSRCNN). This method incorporates an edge-guided modulation mechanism to preserve object boundaries and a Squeeze and Excitation (SE) block to focus on critical structural features. A major benefit of this framework is the use of frozen, pretrained FSRCNN weights, which bypasses the requirement for retraining. Our evaluation on the UTKinect, Middlebury, …

An Intuitionistic Fuzzy Hypergraph Model Enhanced ‎By Forest-Of-Walks Dynamics For Medical Image ‎Segmentation, Brinthaguru Thangaraj, Karthick Palanisamy

Mansoura Engineering Journal

The process of accurately segmenting Urolithiasis and pulmonary nodules from medical images presents significant difficulties because of three main factors which include nonuniform intensity distribution and the presence of weak object borders and the uncertainty caused by anatomical structure overlaps. The study introduces F-Zinhger as a solution to these problems through its application of the Forest of Walks technology. The method uses superpixels as fundamental elements which form a multi-scale hypergraph that establishes hyperedges through three criteria: intensity similarity, spatial proximity, and Z-intuitionistic fuzzy hesitation to capture complex contextual connections. The system incorporates a random walk-based label propagation system. The …

A Hybrid Geospatial And Remote Sensing Methodology For Drought Vulnerability Assessment In Semi-Arid Ecosystems, Kaifi Fakhir Chomani

Mansoura Engineering Journal

The Kurdistan Region of Iraq (KRI) faced significant drought challenges due to global and environmental changes, necessitating drought assessments. Advanced techniques of remote sensing, Geographic Information Systems (GIS), and Analytic Hierarchy Process (AHP) were combined in this research to perform drought vulnerability zonation for KRI. Average annual rainfall, Average number of rainy days, Average annual temperature, slope, elevation, normalised difference water index (NDWI), normalised difference vegetation index (NDVI), land surface temperature (LST), and temperature condition index (TCI) were selected as contributing parameters for drought vulnerability assessments. The considered parameters were weighted using pairwise comparison, and thematic maps were created to …

The Steelerville Case: Applying Criminological Theory To Crime And Police Morale, Shamus Smith

Open Educational Resources

Students use a fictional town’s economic decline and rising crime to evaluate at least two criminological theories and their implications for policy. Role-playing as consultants, they develop research-supported recommendations to reduce crime and improve police morale.

Cross-Domain Antimicrobial Resistance In Poultry Farming: A One Health Assessment Of Antimicrobial Use And Multidrug Resistance In Kiambu County, Kenya, Ann Kangai Munene, Peter Muiruri Mwangi, Lilly Caroline Bebora, Christine Minoo Mbindyo, John Muthini Maingi

All Peer-Reviewed Publications

Background and Aim: Antimicrobial resistance (AMR) has emerged as a major One Health threat driven by inappropriate antimicrobial use (AMU) in humans, animals, and the environment. Poultry production is recognized as a key reservoir of antimicrobial-resistant bacteria, yet few studies in Kenya examine AMU and AMR across interconnected human–animal–environment domains. This study assessed AMU patterns among poultry farmers in Kiambu County and characterized phenotypic resistance in Escherichia coli and Enterococcus spp. isolated from humans, chickens, and chicken environments. Materials and Methods: A cross-sectional study was conducted from May to September 2024, involving 102 poultry farms. Farm demographics and AMU data …

Mapping Robusta Coffee (Coffea Canephora) Cropping Systems In Uganda: A Two-Step Pixel And Sub-Pixel Based Approach With Sentinel-2 Data, Getachew Kebede, Bester Tawona Mudereri, Onisimo Mutanga, Tobias Landmann, John Odindi, Natacha Motisi, Fabrice Pinard, Henri E.Z. Tonnang, Elfatih M. Abdel-Rahman

All Peer-Reviewed Publications

Coffee is a highly valued commodity and a widely consumed beverage, playing an important role in global trade. However, coffee farming landscapes are increasing transitioning into smaller-scale agricultural setups. This transformation highlights the critical need for accurate classification and mapping of coffee cropping systems (CS), especially in countries like Uganda, where dense vegetation and complex terrain present substantial challenges to traditional land survey methods. Moreover, understanding the spatial distribution of Robusta coffee (Coffea canephora) CS is essential for developing site-specific management strategies, guiding extension services, and informing evidence-based policy decisions. To address this gap, the present study aimed to enhance …

Roles Of Cytokines In Modulating Trypanosoma Brucei Rhodesiense Infection Outcomes In Vervet Monkeys, Clarah Jebet, John Kibuthu Thuita, Daniel Masiga, Benedict Owino Orindi, John Oidho, Mark C. Field, Enock Matovu, Vincent Owino Adung’A

All Peer-Reviewed Publications

Introduction:

Human African trypanosomiasis (HAT), caused by Trypanosoma brucei rhodesiense, is categorized as acute due to rapid disease progression but presents varying clinical outcomes. Although the mechanisms underpinning differential clinical progression are poorly understood, both host and parasite factors are implicated. Therefore, we sought to elucidate roles of primate host factors in mediating varying T. b. rhodesiense infection outcomes.

Methods:

Here, we assessed the roles of selected host cytokines in disease progression using a tsetse-mediated infection in a non-human primate (NHP) vervet monkey model that closely mimics HAT and natural infection. We quantified eight cytokines, including TNF-α, IFN-γ, IL-10, IL-6, …

Impact Of Environmental Microparticles On Insect Olfaction, Steve B.S. Baleba, Danube K.N. Wandji, Yves H. Tchiechoua, Komi Mensah Agboka, Iman B. Hassaballa, Victor O. Omondi, Beatrice T. Nganso, Saliou Niassy, Souleymane Diallo, Merid N. Getahun

All Peer-Reviewed Publications

Terrestrial insects underpin key ecosystem services, including pollination, herbivory regulation, decomposition, nutrient cycling, and disease control. These functions depend on chemical communication that guides insects to food, mates, hosts, shelters, and oviposition sites while helping them avoid threats. Environmental microparticles, such as micro- and nanoplastics, tyre wear particles, soot, mineral dust, and agricultural residues, are now widespread across air, soil, vegetation, and indoor environments, exposing insects through contact, deposition, and ingestion. Growing evidence shows that these particles disrupt insect olfaction by adsorbing volatile compounds, blocking antennal sensilla, and interfering with receptor and neuronal processes. These disruptions impair foraging, mating, oviposition, …

Synergistic Impact Of A Colorectal Bundle On Surgical Site Infections In Children, Allen J. Huang, Nicholas A. Long, Owen N. Ferriola, Joan C. Bruce, Douglas J. Fox Iii, Erin M. Morris, Jeannette M. Joly, Carleen V. Cuevas, Akemi Kawaguchi, Kuojen Tsao

Summer Research Program Abstracts

No abstract provided.

Development Of A 3d-Printed Hemodynamic Model To Characterize Doppler Signatures Of Obstructed Tapvr, Michael R. Turner, Maher R. Saadeh, Holly D. Bauser-Heaton, Vahid Serpooshan

Summer Research Program Abstracts

No abstract provided.

A Community-Informed Survey Identifying Research Priorities For Sex Chromosome Aneuploidies, Matthew Fein

Summer Research Program Abstracts

No abstract provided.

Interdependence Of Adoption Decisions Of Agroecological Vegetable Cropping Systems Among Smallholder Farmers In Eastern Africa, Essy C. Kirui, Dickson O. Okello, Michael M. Kidoido, Daniel M. Mutyambai, Komivi S. Akutse

All Peer-Reviewed Publications

Vegetable production plays a vital role in enhancing nutrition and generating income in Kenya, where it is an important component of the agricultural sector. Among the most widely grown vegetables are cruciferous crops, while traditional African vegetables have increasingly gained prominence in recent years. Smallholder farmers account for more than 70% of the country’s total vegetable production. However, they face various complex factors such as extreme climate variability, invertebrate pests, and diseases which reduce productivity, yields and household incomes. They, therefore, often resort to the overuse of synthetic fertilizers and pesticides that could increase their susceptibility to pest resistance, declining …

A Systematic Review And Meta-Analysis Of Mosquito Arboviral Infections Detected Through Xenosurveillance In Africa: A Focus On West Nile, Rift Valley Fever, And Chikungunya Virus Infections, Mxolisi Mgongoma, Armanda Bastos, Abel Ramoelo, David P. Tchouassi

All Peer-Reviewed Publications

This systematic review and meta-analysis comprehensively evaluated the mosquito arboviral infections with West Nile virus (WNV), Rift Valley fever virus (RVFV), and chikungunya virus (CHIV), detected through xenosurveillance, reported in mosquito vectors across Africa in the last 25 years (2000–2024). The study analysed xenosurveillance data from 45 studies conducted with over 115,000 mosquito specimens, and incorporated moderator analyses to assess the influence of trap type, seasonality, regional location, settlement type, and screening methods on virus detection rates. The estimated pooled prevalence of WNV was 1.18% (95% CI: 0.60–3.43%), with higher rates observed in Culex quinquefasciatus and Culex pipiens, particularly in …

Pathways, Outputs And Impact Of Nih-Supported Bioinformatics And Genomics Graduate Trainees In Africa, Daudi Jjingo, Andrew Walakira, Suhaila Hashim, Cisse Cheickna, Ronald Galiwango, Caleb Kibet, Florence N. Kivunike, Gerald Mboowa, Fredrick Elishama Kakembo, Babajide Ayodele, Jean Baka Domelevo Entfellner, Santie De Villiers, Karen Wambui, Segun Fatumo, Tinashe Chikowore, John Mukisa, Alfred Ssekagiri, Nicholas Bbosa, Julius Mulindwa, Samuel Kyobe, Mike Nsubuga, Grace Kebirungi, Eric Katagirya, Savannah Mwesigwa, Ibra Lujumba, Rogers Kamulegeya, Samuel Kirimunda, Stephen Kanyerezi, Shahiid Kiyaga, Ivan Sserwadda, Davis Kiberu, Daniel Masiga

All Peer-Reviewed Publications

Global biomedical and health research is increasingly relying on genomic and computational approaches, largely driven by the increasing volumes of nucleic acid sequencing. Concurrently, epidemiological studies and clinical records are generating enormous amounts of data amenable to disease modeling, machine learning, and artificial intelligence techniques. Bioinformatics and data science expertise is therefore essential for improved population health. Accordingly, in 2012, the US National Institutes of Health (NIH) in partnership with the Wellcome Trust, and with support from the African Society for Human Genetics, initiated the H3Africa (Human Heredity and Health in Africa) consortium. One of its key goals was to …

Effects Of Temperature On The Life-History Traits Of Myzus Persicae And Its Efficiency In Transmitting Potato Virus Y (Pvy) In Potato Crops, Bonoukpoè M. Sokame, Henri E. Tonnang, Heidy Gamarra, Pablo Carhuapoma, Jan Kreuze, Leah R. Johnson, Ali Arab, Peter A. Armbruster, Oswaldo C. Villena

All Peer-Reviewed Publications

Aphids are highly sensitive to temperature changes and play a crucial role in transmitting plant viruses, accounting for the transmission of more than 50% of viruses that cause disease in crops. Among them, Myzus persicae is a major global pest, affecting over 400 plant species and transmitting more than 100 plant viruses, including potato virus Y (PVY), which poses a severe threat to potato crops. This study examines how temperature influences the life-history traits of M. persicae and its efficiency in transmitting PVY. Our research revealed that temperature significantly affects developmental duration, survival, and fecundity of M. persicae. The aphids …

The Career Choices Of Final Year Nursing Students In The United Kingdom: A Qualitative Study., Kevin Hambridge, Frazer Underwood, Gosia Bettache, Matt Carey, Halil Kaya, Lisa Burrows, Rachel Tims, Christian Brailsford

School of Nursing and Midwifery

Aim: The aim of this study is to explore the career choices of final year under-graduate nursing students in the United Kingdom. Background: Worldwide there is a decreasing number of nurses and in the United Kingdom there is a decreasing amount of nursing students. There is sparce evidence relating to the career's choices of nursing students and reasons for those choices. Obtaining a deeper comprehension of these choices may aid healthcare employers, in partnership with universities, to design the future nursing workforce. Design: A qualitative design was used. Methods: Twenty-one final year under-graduate nursing students from across a range of …

Enhancing Offshore Wind Resource Assessment Through Neural Network-Based Hf Radar Data Analysis, Nikolas Martzikos, Matthew Craven, David Walker, Daniel Conley

School of Engineering, Computing and Mathematics

The increasing demand for offshore wind energy underscores the need for accurate wind speed estimation to support the design and operation of offshore wind farms. High-Frequency Radar (HFR), a widely used remote sensing technology in oceanographic research, offers promising potential for wind resource assessment, particularly in areas where conventional measurements are limited. This study explores the application of artificial neural networks (ANNs) for offshore wind speed prediction using HFR-derived data, addressing key challenges in model development and training. A key feature of this approach is the use of a decade-long dataset from the Celtic Sea, off the southwest UK coast, …

Next-Generation Virtual Environment Training For Cybersecurity In The Maritime Logistics Industry: A Position Paper, Tyler Cheng, Rory Hopcraft, Kimberly Tam, Ji-Jian Chin

School of Engineering, Computing and Mathematics

The maritime logistics industry is the most dependent on it in the modern world, yet it is not well protected against cyber risks. Recently, the maritime industry has been transitioning into industry-specific tech, and threats of cyberattacks are increasing as the adoption of technology and automation continues. One of the most effective methods to protect industries and ships from such security incidents, is to train seafarers to mitigate and handle such incidents. However, to the best of our knowledge, we did not find anything that addresses this gap. This article will present the idea and benefits of using virtual environments …

Angle-Based Formation Stabilization And Maneuvers In Port-Hamiltonian Form With Bearing And Velocity Measurements, Ningbo Li, Pablo Borja, Arjan Van Der Schaft, Jacquelien M.A. Scherpen

School of Engineering, Computing and Mathematics

This paper proposes a port-Hamiltonian approach for angle-based formation stabilization and maneuvers using bearing and velocity measurements with an underlying triangulated Laman graph. The corresponding port-Hamiltonian controller is designed using virtual couplings on the errors of angle constraints in angle space. Then, the angle constraints and agent actuators are mapped by the constraint Jacobian, which can be applied to other formation constraints. In addition, to avoid unavailable distance terms in the control law, an estimator is designed based on port-Hamiltonian theory and the property that energy is coordinate-free for different sensor modalities using bearing and velocity measurements, which permits our …

Scope 3 Carbon Emissions Assessment For Manufacturing Smes, Kourosh Halat, Stephen Childe, Nick Golding, John Summerscales

School of Engineering, Computing and Mathematics

This paper addresses the challenges facing managers of Small-andMedium-Size Enterprises (SMEs) when conducting environmental sustainability assessment at the value chain level, particularly Scope 3 Greenhouse Gases GHG) emissions. The paper investigates issues related to data availability and data quality for Scope 3 assessment and identifies dimensions of Scope 3 reliability.Utilising a series of in-depth case study analyses with SMEs in the south-west of England, UK, the paper fills a gap in supply chain sustainability research by identifying practical challenges. The findings show that SMEs encounter persistent difficulties in assessing emissions associated with purchased goods and services and downstream activities linked …

Exploring The Acceptability Of Integrating Dietitians Into Primary Care Dental Services For Children, Lauren Hallewell, Raul Bescos, Zoe Brookes, Tracey Parkin, Robert Witton, Patricia Casas-Agustench

School of Health Professions

BACKGROUND: Dental caries is a common childhood non-communicable disease strongly associated with high sugar intake. Beyond oral health, a poor diet can affect children's growth, development, and overall well-being. While dietary advice is central to preventive dental care, some primary care dental clinics have introduced body mass index (BMI) assessments and further dietary advice to address wider nutritional concerns in children. However, these efforts are often constrained by limited nutrition training, time constraints and concerns about sensitivity. Integrating dietitians into primary dental care may help overcome these barriers by enhancing dietary guidance, supporting broader nutritional needs and facilitating structured BMI …

Usable Authentication: Are We There Yet?, Nathan Clarke, Steven Furnell

School of Engineering, Computing and Mathematics

With technology increasingly embedded in everyday life, the demand for secure and usable authentication methods has never been greater. Traditional password-based systems continue to dominate, despite well-known usability and security challenges. This paper explores the evolution of user authentication technologies, from secret knowledge and tokens to biometrics and emerging approaches such as Passkeys. It critically evaluates the extent to which usability has been achieved, identifying both successes—such as biometrics integrated into smartphones—and persistent issues, including inconsistent guidance, ecosystem dependence, and accessibility barriers. Drawing on academic and commercial developments, the discussion highlights the growing burden on users who must authenticate across …

From Predictions To Explanations: Explainable Ai For Autism Diagnosis And Identification Of Critical Brain Regions: 18th International Joint Conference, Biostec 2025, Kush Gupta, Amir Aly, Emmanuel Ifeachor, Rohit Shankar

School of Engineering, Computing and Mathematics

Autism spectrum disorder (ASD) is a neurodevelopmentalcondition characterized by atypical brain maturation. However, the adaptationof transfer learning paradigms in machine learning for ASD researchremains notably limited. In this study, we propose a computeraideddiagnostic framework with two modules. This chapter presents atwo-module framework combining deep learning and explainable AI forASD diagnosis. The first module leverages a deep learning model finetunedthrough cross-domain transfer learning for ASD classification. Thesecond module focuses on interpreting the model’s decisions and identifyingcritical brain regions. To achieve this, we employed three explainableAI (XAI) techniques: saliency mapping, Gradient-weighted Class ActivationMapping, and SHapley Additive exPlanations (SHAP) analysis.This framework demonstrates that …