Digital Commons Network^™

Exchanging Genes Within A City: Analysis Of Pollen Flow Patterns In A Narrow Endemic Plant Species Threatened By Urbanisation, Nicola Delnevo, Andrea Piotti, Eddie J. Van Etten, William D. Stock, David L. Field, Margaret Byrne

Research outputs 2022 to 2026

Human-driven habitat fragmentation is known to disrupt gene flow in a wide range of species. However, its consequences for endemic plant species that depend on specialised invertebrate pollinators remain poorly understood. Although honeybees are capable of travelling considerable distances while foraging, many small-bodied native bee species lack the capacity to expand their foraging ranges or cross anthropogenic barriers, rendering habitat fragmentation the most significant threat to these ecological interactions. In many long-lived plants, the time since fragmentation has not been long enough for detectable changes in the genetic composition of standing populations. Changes in dispersal patterns observed in seedlings may …

Self-Management Challenges And Psychosocial Support Needs In Clean Intermittent Catheterization: A Qualitative Study Of Individuals With Neurogenic Bladder And Caregivers, Lianyu Zou, Xiaomei Wu, Shun Chen, Shuluan Feng, Xiaohua Huang, Weiting Liu

Research outputs 2022 to 2026

Background – Clean intermittent catheterization (CIC) is widely regarded as the preferred approach to bladder management for individuals with neurogenic bladder (NB). Nevertheless, a considerable gap persists between evidence and clinical practice: patients and caregivers frequently encounter self-management barriers that compromise clinical outcomes during CIC. This qualitative study explores these barriers to provide an empirical foundation for developing tailored strategies that improve quality of care. Design – A descriptive qualitative study. Methods – From August to October 2025, a convenience sampling method was employed to recruit 16 participants individuals with NB or their long-term caregivers from the Department of Rehabilitation …

Partisan Differences In Risk-Taking In A Simulated Pandemic, Jan K. Woike, Sebastian Hafenbrädl, Patricia Kanngiesser, Ralph Hertwig

School of Psychology

Responses to COVID-19 in the United States were split along partisan political lines throughout the pandemic. People on the political left tended to take the medical threat more seriously and were more likely to adopt preventive health behaviors than those on the political right, resulting in clear differences in state-level policies and health consequences. Here, we examine the origins of these differences, investigating whether they are based on interindividual differences or in party dynamics. Two groups of participants (N=819), who had voted either for Donald Trump or Hillary Clinton in 2016, played the Transmission Game. Players made repeated decisions in …

Evidence Base To Inform Health Service Configuration For Abortion Provision: The Sacha (Shaping Abortion For Change) Multi-Component Study, Kaye Wellings, Rebecca S. French, Annette Aronsson, Paula Baraitser, Sharon Cameron, Caroline Free, Louise Keogh, Maria Lewandowska, Patricia Lohr, Rebecca Meiksin, Ona Mccarthy, Clare Murphy, Wendy Norman, Melissa Palmer, Jennifer Reiter, Natasha Salaria, Rachel Scott, Jill Shawe, Sally Sheldon, Geoff Wong

School of Nursing and Midwifery

Background: Significant changes to the nature and context of abortion provision are taking place in the United Kingdom. Empirical evidence is needed to guide efforts to respond to these changes. Objective(s): To provide an evidence base to inform optimal configuration of health services and systems in response to current and future changes in abortion provision in the UK. Design and methods: Observational study comprising five integrated components: (1) a realist review to generate evidence to guide optimal abortion provision and a scoping review of interventions aimed at preparing non-specialist health professionals to provide abortion care and support; (2) country-based case studies identifying transferable …

Evaluating The Collision-Coalescence Process In Idealized Cloud Convection Using Large-Eddy Simulations With Lagrangian Microphysics, Yangze Ren, Kamal Kant Chandrakar, Fan Yang, Raymond Shaw

Michigan Tech Publications

Drizzle initiation through the collision and coalescence of cloud droplets plays a crucial role in warm cloud precipitation. Recent theoretical studies suggest that the influence of collisional growth on the droplet size distribution can be quantified by a non‐dimensional drizzle number (Dz). Here, large‐eddy simulations with Lagrangian microphysics are employed to evaluate the theory by simulating a tall convection‐cloud chamber under various conditions. Results show that the smaller the Dz, the larger the impact of collisions on the right tail of the droplet size distribution, consistent with the theory. The simulations confirm that the collision rate can be estimated from …

Breathing Kagome Lattice-Based Nb3i8 Monolayer: Theoretical Insights Into Enhanced Hydrogen Evolution Catalysis, Narender Kumar, Radha Somaiya, Ravindra Pandey, Nacir Tit

Michigan Tech Publications

Photocatalytic water splitting is a promising strategy for clean energy production, but its efficiency is restricted by poor light absorption, charge recombination, and slow reaction kinetics in photocatalytic materials. To address these challenges, a breathing Kagome lattice-based Nb3I8 monolayer is considered in the present study. Its photocatalytic performance is assessed via descriptors including the effective d-band center, spin-dependent carrier mobility, Gibbs free energy, and exchange-current density. The results based on density functional theory predict that the Nb3I8 monolayer is a type II magnetic semiconductor, with spin-up and spin-down bandgap energies of 1.06 and 1.77 eV, respectively. The application of biaxial …

Quantum Dot Solar Cells: Background, Progress, And Perspective, Kumar Neupane, Jeff Kabel, Join Uddin, Raksha Dubey, Rojina Ojha, Dongyan Zhang, Yoke Khin Yap

Michigan Tech Publications

The discovery of quantum dots (QDs) earned a Nobel Prize and has led to widespread applications in research and technology. In this review, we focus on the use of QDs in solid-state solar cells (QDSCs). We begin with an overview of the basic principles of SCs. Then, we discuss how device architecture has developed over recent decades, setting the stage for the final section on fourth-generation solar cells (Perspective section). We also highlight progress in material development, starting with lead- and cadmium-based QDs and progressing to more recent carbon- and perovskite-based QDs. Additionally, we review materials used for electron-transport layers …

A Model Intercomparison Study To Investigate Mixing Characteristics In Non-Precipitating Stratocumulus Clouds, Fan Yang, Kyoung Ock Choi, Kamal Kant Chandrakar, Fabian Hoffmann, Pei Hou, Steve Krueger, Chunsong Lu, Mikhail Ovchinnikov, Yangze Ren, Shin Ichiro Shima, Peng Wu, Chongzhi Yin, Zeen Zhu, Seong Soo Yum

Michigan Tech Publications

Recent aircraft observations of marine stratocumulus clouds consistently showed that cloud microphysical relationships vary with altitude, indicating inhomogeneous mixing characteristics near cloud top and homogeneous mixing characteristics in mid-levels of clouds. Here, we conduct model intercomparison of an idealized, non-precipitating stratocumulus cloud to evaluate model consistency and examine whether simulations can reproduce the observed mixing characteristics. The results show that eleven large-eddy simulations with various dynamics and microphysics schemes show good agreement on the thermodynamical, microphysical, and dynamical properties of the stratocumulus-topped boundary layer in a steady state. The inter-model spread in steady-state liquid water path is significantly reduced compared …

Impact Of Plasma Ptau181 Levels On Clinician Diagnostic Confidence And Management In Memory And Cognition Clinics: A Multi-Site Before-And-After Study, Johannes C. Michaelian, Azadeh Feizpour, James C. Vickers, Jane E. Alty, Jessica M. Collins, Vincent Doré, Catriona Ireland, Anna E. King, Ralph N. Martins, Michael Woodward, Sharon L. Naismith, Christopher C. Rowe

Research outputs 2022 to 2026

Introduction: Recent advances allow blood tests to detect key proteins linked to Alzheimer's disease (AD). Methods: In this before-and-after study across three Australian memory and cognition clinics, we evaluated the impact on clinicians' diagnostic confidence and management following disclosure of routine patients' AD probability, using predefined plasma phosphorylated tau 181 (pTau181) thresholds set at 90% sensitivity and 90% specificity for amyloid-beta (Aβ) positron emission tomography (PET) positivity. Results: One hundred thirteen participants (mean age: 71.2 ± 8.4; mean Mini-Mental State Examination score: 27.7 ± 2.5) with dementia (n = 17, 15.0%), mild cognitive impairment (n = 48, 42.5%), and subjective …

Setting Research Priorities For The Use Of Digital Technology In The Self-Management Of Heart Health: The Results Of The James Lind Priority Setting Partnership, Lis Neubeck, Simon Nichols, Nicola Straiton, Louise J. Dunford, Amitava Banerjee, Susan Dawkes, Donna Fitzsimons, Maria Hayes, Alistair Lawson, Abigail A. Lyons, Mary Mcauley, Jill Mclaggan, Richard Mindham, Nicholas L. Mills, Rakesh Modi, Alice Pearsons, Amanda Pitkethly, Fiona E. Strachan, Coral L. Hanson

Research outputs 2022 to 2026

Aims: There are wide inequalities in access to cardiovascular care, and risk factors such as obesity, high blood pressure, and physical inactivity are often not well managed. We aim to identify the most important questions about how digital technologies can help people and their carers prevent cardiovascular disease and improve access to care. Methods and results: A priority setting partnership that aimed to generate a top 10 list of research priorities for the use of digital technology in the prevention and management of heart disease and heart conditions in the UK and Ireland, with equal input by people with lived …

Intelligent Deep Learning-Based Sign Language Translation System, Nada Rasem Shahin

Dissertations

The Deaf and Hard of Hearing (DHH) community uses sign language as a primary means of communication. However, the shortage of sign language interpreters and the existence of hundreds of sign languages limit accessibility and inclusion. Sign Language Machine Translation (SLMT) systems present a promising solution for bridging the communication gap between the DHH and the hearing individuals, supporting inclusive societies. In smart cities, such systems play an essential role in improving the quality of life on a community level. In particular, as the population’s well-being is critical, developing intelligent assistive technologies, such as SLMT systems, is necessary to provide …

Efficient Energy Management In Networked Microgrids Using Multi-Agent Deep Reinforcement Learning In The Presence Of Uncertainties, Ayodele Benjamin Chukwuyem

Dissertations

Microgrid technology is essential in facilitating the transition to smart energy grids in developed countries and mitigating energy poverty in developing countries, particularly in areas where grid extensions are not feasible. Recently, the concept of networked microgrids (NMGs) has garnered tremendous attention due to the plausibility of interactions among interconnected microgrids leading to power networks that are more resilient, reliable, and stable. However, because each microgrid has diverse distributed generation resources (renewables and controllable generators) and each microgrid operator (MO) has different objectives, coordinated energy management is required to satisfy local and system-wide goals under conditions with significant uncertainty. Existing …

Fully Decentralized Hierarchical Federated Learning At The Edge With Post-Quantum Secure Communication, Tariq Qayyum

Dissertations

Federated learning (FL) enables collaborative model training without centralizing raw data, but deploying FL at scale in real edge environments remains challenging because iterative training and aggregation must operate over heterogeneous, resource-constrained, and often mobile devices with time-varying connectivity. Conventional hierarchical federated learning (HFL) partially mitigates communication cost by introducing fog/edge aggregation, yet many designs retain cloud-based global aggregation and cloud-centric coordination. This places wide-area network latency on the critical path of every training round, creates a single point of failure, and limits responsiveness as model sizes and federation scale grow. Moreover, moving coordination and aggregation closer to the edge …

A Low-Noise And High-Gain Integrated Photoplethysmography Sensor For Continuous Vital Signs Monitoring, Neethu Mohan

Dissertations

Photoplethysmography (PPG) sensing is an important technology used for measuring health parameters like, heart rate, respiratory rate, blood oxygen saturation, and blood pressure (BP). The PPG sensing is used for individuals who have to periodically monitor their health due to chronic health conditions. The basic requirements of a wearable PPG sensor include non-invasiveness, prolonged battery life, and being userfriendly. These type of sensors have great demand in the healthcare applications and there is a significant rise in the demand of these sensors. The basic objective of these PPG sensors is to make the continuous vital health monitoring easier without the …

A Comparative Study On Performance Of Iot-Driven Ml-Enabled Forecasting Models For Efficient Air Quality Monitoring, Bara Ksiksi

Theses

Air pollution is one of the most critical environmental challenges affecting public health globally, responsible for approximately 4.2 million premature deaths annually according to the World Health Organisation. This thesis presents a comparative study of IoT-driven machine learning forecasting models for air quality monitoring in Abu Dhabi, UAE, introducing a zonal approach combined with satellite-based spatial validation. The primary objective is to evaluate forecasting performance across three distinct activity zones using ground station data from the Environment Agency Abu Dhabi (EAD), and to incorporate a spatial validation component using satellite imagery to assess the consistency of ground-based predictions at a …

Ideals And Lattices In Number Fields, Sarah Ali Alyammahi

Theses

This thesis investigates algebraic number fields and their rings of integers, which

generalize the ring of integers ℤ in ℚ. The study focuses on ideals, units, and ideal class

groups, which describe the arithmetic structure of number fields and the failure of unique factorization. Key invariants such as the norm, trace, and discriminant are developed and applied, with particular emphasis on quadratic number fields and classical examples such as the Gaussian and Eisenstein integers. Some explicit computations of ideal class groups are carried out. The thesis also explores connections with lattice theory by interpreting rings of integers as lattices and …

Traditional And Machine-Learning Equalization Techniques For Bandwidth-Limited Short-Reach Optical Communication Channels, Abdullah Khawatmi

Theses

This thesis investigates equalization techniques for bandwidth-limited short-reach optical communication systems, with a focus on Visible Light Communication (VLC) and Step-Index Plastic Optical Fiber (SI-POF) links. Commercial light-emitting diodes and photodiode receivers impose severe bandwidth constraints, inter-symbol interference, and noise sensitivity, which fundamentally limit achievable data rates. The work addresses these impairments through systematic evaluation of traditional digital signal processing–based equalizers and modern machine-learning-based post-equalization methods. The primary aim of this thesis is to enhance the achievable data rate and reliability of commercial short-reach optical links while maintaining practical computational complexity. Specifically, the objectives are to (i) design and experimentally …

Llm-Driven Mission Control And Autonomous Planning For Search-And-Rescue Uavs: A Simulation-Based Evaluation, Naser Bader Alsaedi

Theses

Unmanned aerial vehicles (UAVs) are increasingly used in search‑and‑rescue (SAR) missions, yet many systems still rely on fragmented software where mission design, perception, and flight control are configured separately. This thesis examines whether a unified AI‑driven framework can reduce configuration effort and operator workload in UAV‑based SAR operations. The proposed system integrates natural‑language mission specification using a large language model (LLM) (LLaMA 3.1), autonomous coverage planning, YOLOv8‑based victim detection, and PX4/MAVSDK control within a single architecture. Operators describe missions through free‑form text or a graphical interface; the model converts these descriptions into structured mission parameters that are automatically planned and …

Comparative Evaluation Of Five Bacterial Strains For The Fermentation Of Camel Milk, Sifatun Nesa Ali

Theses

In this study, the comparative fermentation performance of lactic acid bacteria Streptococcus thermophilus, Lactobacillus delbrueckii subsp. bulgaricus, Lb. helveticus, Lb. casei, and Lactiplantibacillus plantarum in Camel Milk (CM) and Bovine Milk (BM) was investigated. Fermentations were carried out at 42°C for 48 hours, and was monitored through bacterial growth, titratable acidity, pH evolution, proteolytic activity, microstructural properties, and rheological characteristics. Although comparable bacterial viability was observed in CM and BM, acidification kinetics varied significantly between CM and BM (p < 0.05). Proteolysis was significantly higher in fermented CM than in BM (p < 0.001), with consistently greater o-Phthalaldehyde Assay (OPA) values in CM across all strains during fermentation (p < 0.001). Scanning electron microscopy revealed more porous, loose protein matrices in fermented CM than in BM, which supports the rheological results showing weaker gel networks and lower rheological strength in fermented CM. Among the tested bacteria, Lb. casei demonstrated superior adaptability, enhanced viability, balanced acidification, and favorable rheological properties in both milks. Overall, the results of this thesis demonstrate strain-specific fermentation responses and support the possible suitability of different starter cultures for improving the technological performance of fermented camel milk products.

Modeling And Autonomous Control Systems For A Delivery Drone Application, Dana Helal Alnuaimi

Theses

This thesis focuses on the development of a multi-drone navigation and control system, aiming to enhance payload capacities beyond the limits of single-drone systems. By integrating multiple drones to work collaboratively as a unit, this study addresses the challenges associated with lifting and transporting heavier payloads.

The primary objective is to design and evaluate a multi-drone system capable of working in tandem to transport larger payloads efficiently. The research aims to develop robust control algorithms, supported by system identification for dynamic modeling, and navigation strategies to enable effective coordination between drones.

The study employs a combination of simulation and real-world …

Analysis Of A Coaxial Transmission Line Filled With An Orthorhombic Dielectric-Magnetic Medium, Fathima Manikunnath Abdul Akbar

Theses

Coaxial transmission lines are fundamental means for Transverse Electromagnetic (TEM) wave propagation in RF, microwave and high-speed electronic systems. The study of transmission lines is often familiar when they are filled with isotropic materials; however modern engineered direction dependent materials reshape field distributions. In this thesis, we consider a coaxial transmission line of an inner radius and outer radius b filled with an orthorhombic dielectric-magnetic material, which is described by two anisotropy parameters αx and αy. The potential and field distributions are studied in relation to the ratio b/a as well as the anisotropy parameters αx and αy. Due to …

Breath-Based Detection Of Liver Cancer Biomarkers Using An Swcnt-Fet Nano-Biosensor: Quantumatk, Mohamed Mohieb Rashdan

Theses

Early detection of liver cancer remains limited by the slow pace and invasiveness of current testing methods. This study proposes a single-walled carbon nanotube field-effect transistor (SWCNT-FET) designed to detect hexanal—a volatile organic compound (VOC) elevated in liver cancer—directly from exhaled breath. The device is modeled in QuantumATK using a semi-empirical Extended Hückel Hamiltonian within the non-equilibrium Green's function (NEGF) framework, emphasizing realistic contact physics by employing metallic SWCNT electrodes instead of conventional metal films. Zigzag channels with (11,0) and (12,0) chiralities are examined to analyze how geometry and contact matching influence charge transport. Simulations include current–voltage (I–V) characteristics and …

Transport Of Quantum Walks In Electric Fields, Yousef Mohammad Yousef Salah

Theses

This thesis presents an analysis of transport in one-dimensional discrete-time quantum walks (DTQWs) on the Hilbert space ℓ²(ℤ) ⊗ ℂ². Quantum walks serve as fundamental models of coherent quantum transport and exhibit ballistic spreading driven by superposition and interference. The primary focus of this work is the review and derivation of sharp maximal velocity bounds for several classes of quantum walk step operators, including the shift-coin walk, the split-step walk, and models with constant as well as position-dependent coin operators. We establish general a priori bounds that remain valid beyond the translation-invariant regime. For homogeneous models, Fourier and spectral analysis …

Development Of A Novel Cfd Approach For Predicting Multiphase Flow Enhanced By Machine Learning, Abdulrahman Elazazi Salem

Theses

Accurate estimation of interface orientation is crucial for ensuring both the accuracy and robustness of Volume of Fluid (VOF) schemes in multiphase flow simulations, especially when using non-uniform Cartesian meshes. Conventional gradient reconstruction approaches, such as least-squares (LSQ) methods, often suffer from significant errors and strong oscillations on highly stretched grids. This work proposes a grid-transferable, learning-based methodology that predicts interface unit normal vectors directly from the local volume-fraction field on nonuniform structured Cartesian grids using a feedforward neural network. The methodology extends earlier work originally developed for uniform grids, which is first reproduced to assess how performance deteriorates in …

Study Of The Effect Of Biodiesel Derived From Jojoba Oil With Alcohols Blends On Diesel Engine Performance, Exhaust Emissions, Vibration, And Noise, Yassir Abdelrahman Elbashier

Theses

This study presents a mutual investigation on the properties of the fuels and the performance of an engine using biofuels from mixtures of jojoba oil biodiesel with alcohols. The work consists of mainly two phases, examining the properties of the jojoba biodiesel-alcohols mixtures and the performance and emission behavior in a single piston diesel engine. A base mixture of 50% jojoba biodiesel and 50% diesel produced, and this was fractionally mixed with 5, 10, and 20% methanol and with 5, 10, and 20% diethyl ether (DEE). The rheological properties namely viscosity and shear stresses of all biodiesel blend mixtures were …

The Impact Of Social Determinants Of Health On The Emotional Well-Being Of Lgbtq Young Adults, Bridget J. Mantooth-Urso

Electronic Theses and Dissertations 2020 - Present

The current study examined whether neighborhood-based social determinants of health (SDOH) were associated with emotional health outcomes among sexual minority young adults ages 18–29, and whether perceived social support mediated this relationship. SDOH refers to the conditions in which individuals are born, grow, live, work, and age, including neighborhood and built environment characteristics that shape access to resources, safety, and well-being. Emotional health in this study was operationalized through self-reported symptoms of depression and anxiety, while social support represented perceived availability and quality of interpersonal resources that may buffer the impact of structural disadvantage. This study utilized a non-experimental, cross-sectional …

Ai Models As Cultural Beings: Investigating Ai Cultural Biases And The Impact Of Cultural Alignment On Human-Ai Creative Collaboration, Choon Ngee Tan, Meng Han, Roy Y. J. Chua, Chi-Ying Cheng

Research Collection Lee Kong Chian School Of Business

Existing research on AI cultural biases predominantly focuses on Western models, overlooking critical gaps in non-Western models. We conduct a comparative analysis of AI models – ChatGPT (U.S. developed) and ErnieBot (China developed) – from different cultures to investigate how corresponding cultural biases manifest in their outputs. Additionally, we examine how cultural alignment between human users and AI models impacts their collaborative creative performance and the underlying psychological mechanisms. In Study 1, multi-choice prompt with zero-shot technique was used to evaluate cultural biases in four widely used AI models – ChatGPT-3.5/4, ErnieBot-3.5/4 – comparing their responses to established cultural psychometric …

Ai, Antitrust, And The Marketplace Of Ideas, Maurice E. Stucke

Fordham Law Review

No abstract provided.

Minimal Success: The Consequences Of Mandatory Minimums In Youth Sentencing, Maya Chrobot

Fordham Law Review

In New York State, children as young as thirteen can be processed as adults and sentenced to mandatory minimum sentences. Mandatory minimum sentences require judges to sentence the defendant to a statutorily set minimum term of imprisonment. Practitioners, judges, and researchers question the efficacy of mandatory minimum sentences, finding that they are ineffective at deterring crime, decreasing bias in sentencing, and increasing community safety. Additionally, there is clear evidence about the damaging effects of incarceration on young adults. Instead of functioning as rehabilitative punishment, incarceration leads young adults to experience poor mental and physical health outcomes upon release, and they …

State Intervention In Local Zoning: Lessons From Housing Applied To Data Centers, Matthew De Boer

Fordham Law Review

There is growing regulatory tension at the intersection of data center development and local land use law. As states aggressively court data centers with tax incentives and economic policies, they have largely declined to regulate where and how these facilities are sited. Local governments, left to absorb the consequences, have responded unevenly, attempting to fit extraordinary land, water, power, and noise-intensive data centers into zoning frameworks designed for far less demanding industrial uses. The result has been a cycle of uncertainty and conflict: developers face unpredictable approvals, moratoria, and litigation, while residents bear escalating infrastructure strain, environmental impacts, and diminished …