Digital Commons Network^™

Flight System Development For A Bio-Inspired Rotating Empennage Experimental Unmanned Aerial Vehicle, Ashton Gilbert

All Graduate Theses and Dissertations, Fall 2023 to Present

Unmanned aerial systems, commonly known as drones, are increasingly used for research, environmental monitoring, and testing new aircraft concepts. Many commercially available drone flight controllers work well for standard aircraft designs, but they can be difficult to adapt for experimental vehicles that use unconventional control methods or require detailed monitoring during testing. This creates challenges for researchers who need flexible and reliable tools to safely evaluate new flight technologies. This work presents the development of a custom drone flight control system designed specifically for experimental research. The system integrates custom electronics and software that allow researchers to easily modify control …

A Critical Review Of Pharmaceutical Pollutants In Soil And Air: Ecotoxicological Impacts On Animal, Plant And Microbial Communities - Health Hazards And Waste Management, Md Faisal Amin, Md. Saydur Rahman

School of Integrative Biological & Chemical Sciences Faculty Publications

Pharmaceutical contamination in soil and air has become a critical environmental concern due to its widespread sources, complex behavior, and long-lasting ecological impacts. This review comprehensively explores the presence, fate, and effects of pharmaceutical compounds in soil, highlighting their entry routes, environmental persistence, and biological consequences. Pharmaceuticals infiltrate terrestrial and aquatic environments through various pathways, including agricultural application, pharmaceutical manufacturing waste, sewage sludge, hospital and household discharges, irrigation with contaminated water, and atmospheric deposition. A wide range of drug classes, such as antibiotics, analgesics, non-steroidal anti-inflammatory drugs, antidepressants, anticancer drugs, and hormones, have been identified in both soil and air …

Bayesian Linear, Heteroskedastic, Multilevel, And Dynamic Models For Assessing The Effects Of Policy Uncertainty, Green Finance, Innovation, And Environmental Stringency On Sustainable Economic Growth In Oecd Economies, Md Qamruzzaman, Abdulrahman Alomair, Abdulaziz S. Al Naim, Sylvia Kor

Student Publications [Scholarly]

This study analyzes how policy uncertainty, green finance, green innovation, and the stringency of environmental policy affect sustainable economic growth in OECD member countries from 1996 to 2023. Given the growing evidence that advanced economies are facing structural lock-ins, a lack of coherent policy credibility, and insufficient financial and innovative capabilities, the current study integrates these factors into a coherent empirical framework that continues to prevent disintegration in the current literature. Using environmentally adjusted multifactor productivity as a proxy for green economic growth, the analysis employs a panel of Bayesian econometric models that include linear, heteroskedastic, multilevel, random-effects, and panel …

Assessing Future Drought Scenarios In Rangpur, Bangladesh Using Cmip6 Climate Projections And Drought Indices, Mijanur Rahman, Hossain Al Mahbub, Mst Sanjida Alam, Janifer Alam, Nusrut Sharmin, Md Naim Molla

Student Publications [Scholarly]

Climate-induced drought has become a growing concern across South Asia as rising temperatures and monsoon variability intensify hydroclimatic stress. This study evaluates historical (1979–2014) and future (2015–2100) hydroclimatic conditions in Rangpur using observed data and CanESM5 projections for three CMIP6 scenarios (SSP1-1.9, SSP2-2.6, SSP5-8.5). Multi-scale Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were applied to detect droughts, while Tmax and Tmin Z-scores quantified heat anomalies and compound drought–temperature events. Historical records show strong rainfall variability with no significant long-term trend, but significant warming particularly in Tmin indicating increasing evaporative demand. Future projections reveal moderate precipitation increases (+ …

Understanding Chatbot-Assisted Collaborative Learning Among Female Undergraduate Students, Mohammad Amin Kuhail, Ahmed Shuhaiber, Sinan Salman, Nazik Alturki

All Works

Computer programming can be daunting for beginners due to complex concepts and syntax. Traditional teaching methods, while engaging through gamification and active learning, often lack personalized approaches. Recent advancements in artificial intelligence (AI), particularly large language models (LLMs), present new possibilities for personalized and interactive learning environments. This study introduces a chatbot-assisted collaborative learning environment (CCLE) that leverages an LLM (GPT-4) to enhance collaborative programming education. The CCLE enables real-time guidance and collaboration through natural language interactions, allowing students to work together on programming tasks, edit code collaboratively, and engage with both peers and the educational chatbot. We conducted an …

A Robust Approach For Olive Leaf Disease Detection In Uncontrolled Environments, Rima Grati, Khouloud Boukadi, Emna Ben Abdallah, Ahmed Seffah

All Works

Detecting diseases in olive leaves is crucial for maintaining tree health and ensuring stable olive production. Early signs of infection often appear on the leaves, making them a key indicator for timely disease detection and intervention. Traditionally, farmers rely on visual inspection or laboratory tests to diagnose plant diseases. However, recent advancements in deep learning (DL) have significantly improved the accuracy and efficiency of olive leaf disease diagnosis. Numerous studies in the literature have explored this task using CNN-based architectures and, more recently, Vision Transformers. While these models have shown promising performance on benchmark datasets, they are often trained and …

Fair And Explainable Educational Recommendations With A Hybrid Graph-Gru Framework, Edmund Evangelista, Syed M.Salman Bukhari

All Works

Artificial Intelligence (AI) recommender systems are increasingly used in education to personalize learning and help students navigate large collections of digital learning resources. However, many existing approaches emphasize predictive accuracy over fairness, robustness, diversity, and transparency. This creates an important educational challenge. The students with limited participation histories may receive less reliable support, while highly popular resources may dominate recommendation lists and limit access to other useful learning materials. To address this challenge, this study aims to develop and evaluate a responsible educational recommender framework that supports personalized learning resource navigation while making recommendation behavior more fair, stable, diverse, and …

The Economics Of Modern Basketball Fandom, Holden Velasco

Capstones

In an increasingly money-sucking economy, many Americans are feeling the aching of their wallets. Basketball, once serving as an escape from the outside world, has now turned into a money-making machine where fans are paying to keep it running. It’s inescapable, whether it’s the rising costs to watch the professionals, forking thousands of dollars for children to play or sports gambling being plastered everywhere. Basketball no longer feels like basketball.

Enhancing Teachers’ Intercultural Literacy: Examining The Impact Of A Fulbright-Hays Group Projects Abroad Program To Indonesia, Paul R. Wallace

Journal of Global Education and Research

The Fulbright-Hays Group Projects Abroad (GPA) Program offers institutional grants to support overseas experiences and curriculum development for educators. The study reported here focused on changes in the intercultural literacy of participants involved in a 4-week Fulbright-Hays GPA Program to Indonesia. Participants in this study included K-12 teachers from public schools and teacher education majors. Before and after traveling to Indonesia, eight participants completed a self-assessment of intercultural literacy, which measured competencies, understandings, attitudes, language proficiencies, participation, and identities deemed necessary for successful living and working in a cross-cultural environment. This article presents the results of the assessment survey, along …

Changing Expectations In Higher Education Post-Pandemic, Gregory R. Mackinnon, Tyler Maclean, Mohamad El Maouch, William Yuan, Zhao Kaibin, Bi Dandan, Marwa Saab

Journal of Global Education and Research

A sample of higher education students in Canada and China was surveyed and interviewed to ascertain any changes in their educational expectations given their experiences with emergency remote teaching during the pandemic. In addition, the instructors of these students were interviewed to corroborate student feedback. The research suggested that students in Canada and China expressed expectations of increased flexibility and improved pedagogy. Whereas Canadian students were overtly demanding of the instructor and the educational system, Chinese students were comparatively subtle in their expectation that the post-pandemic level of support be maintained. The primary concern of the Chinese cohort was a …

Advancing Blended Education: Caribbean Lecturers’ Reflective Narratives Of Caution, Creativity, And Change, Mia A. Jules, Donna-Maria B. Maynard, Grace A. Fayombo, Jason E. Marshall, Tanya Newton, Kamilah Hutson, Amanda Kellman, Cherise Bynoe, Mikaila Collymore, Jo-Ann Prosper-Chase, Laura Lee Foster, Adicia Clarke

Journal of Global Education and Research

Blended teaching requires lecturers to constantly self-reflect on their pedagogical practice to enhance student learning. However, there is yet to be a significant corpus of literature that highlights the cognitive resources that lecturers in higher education should possess to effectively use blended learning strategies. It is important to understand the intellectual resources required for blended pedagogy so that such capabilities can be fostered during faculty-training programs; ultimately resulting in innovative strategies to ensure quality learning outcomes and the advancement of university-level blended teaching mandates. This qualitative case study explored how twelve Caribbean lecturers experienced and navigated the teaching process in …

Green Waste Biochar And Plant Growth-Promoting Bacteria Enhance Tomato Growth Under Combined Nutrient Deficiency And Salinity Stress, Soumaya Tounsi-Hammami, Munawwar Ali Khan, Mahra Alqemzi, Salama Ali Almehairi, Aneesa Rasheed Anwar

All Works

This study characterized a green-waste-derived biochar from date palms and ghaf trees and investigated its potential as a soil amendment with halotolerant Bacillus spp. to improve tomato seedling quality under dual stress of salinity and nutrient deficiency. Biochar was produced through pyrolysis at 450 °C and then characterized for yield, pH, electrical conductivity, proximate analysis, surface morphology, energy-dispersive X-ray spectroscopy, and heavy-metal content. Its effectiveness was tested both alone and in combination with a Bacillus sp. mix, using a completely randomized design with varying NPK fertilizer levels and saline irrigation. Tomato seedlings were evaluated 45 days after planting for various …

A Deep Learning Ensemble Framework For Multi-Subtype Renal Tumor Classification Using Contrast-Enhanced Ct, Hisham Abdeltawab, Ahmed Alksas, Mohamed Ghazal, Ashraf Khalil, Norah Saleh Alghamdi, Rasha T. Abouelkheir, Ahmed Elmahdy, Mohamed Abou El-Ghar, Sohail Contractor, Ayman El–Baz

All Works

Renal cell carcinoma (RCC) is considered the most aggressive and common form of renal cancer. Therefore, early detection is crucial to ensure appropriate and effective treatment planning. In our study, we propose a novel computer-aided diagnostic (CAD) approach which incorporates a deep learning ensemble to differentiate between five renal tumor subtypes, utilising the modality of contrast-enhanced computed tomography (CE-CT). The addressed renal lesions are malignant tumors (chromophobe RCC (chRCC), papillary RCC (pRCC), and clear cell RCC (ccRCC)) and benign tumors (renal oncocytoma (RO) and angiomyolipoma (AML)). Our study includes 280 patients who underwent renal biopsy, 112 patients were diagnosed with …

Integrating Machine Learning And Explainable Ai For Employee Attrition Prediction In Hr Analytics, Maytha Al-Ali, Majed Alwateer, Shatha Abed Alsaedi, Hossam Magdy Balaha, Mahmoud Badawy, Mostafa A. Elhosseini

All Works

Employee attrition poses significant challenges to organizations, impacting productivity, morale, and financial stability. Predicting attrition and understanding its underlying drivers are critical for implementing effective retention strategies. In this study, we propose a comprehensive framework that utilizes advanced machine learning techniques to predict employee attrition and job change likelihood. The framework integrates robust preprocessing pipelines, state-of-the-art predictive models, and explainability tools such as SHAP (SHapley Additive exPlanations) to ensure transparency and fairness in HR analytics. By addressing key challenges such as class imbalance, feature selection, and model interpretability, our approach provides actionable insights for proactive talent management. We evaluate the …

Radio Frequency Tagging–Enabled Patient Monitoring: Integrating Mobility Tracking With Early Warning Systems For Enhanced Safety, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Abhishek Dwivedi

All Works

Ensuring patient safety in healthcare environments requires continuous monitoring systems capable of identifying early warning signs of clinical risk. Traditional surveillance methods often fail to capture meaningful patterns in patient movement, limiting their ability to prevent incidents such as falls, prolonged immobility, or unnoticed health deterioration. Radio Frequency Tagging technology has been increasingly adopted for real-time patient tracking; however, existing systems are generally limited to location detection and lack predictive insights into patient behaviour. To overcome these limitations, this study presents a Radio Frequency Tagging-based patient monitoring framework that integrates mobility tracking with an early warning mechanism to enable proactive …

The Association Between Cyber Behaviors And Hedonic And Eudaimonic Well-Being: The Moderating Role Of Personality Traits, Areej Elsayary, Juan Calmaestra, Mercedes Gómez-López

All Works

The increasing integration of digital technologies into everyday life has intensified engagement in various cyber behaviors, raising important questions about their relationship with individuals' well-being. This study examined the associations between online moral disengagement, problematic internet use (compulsive internet use), benign and toxic disinhibition, cyberaggression, and cybervictimization with both hedonic and eudaimonic well-being among emerging adults in the United Arab Emirates. Furthermore, it explores the moderating role of personality traits in these associations. Data were collected from 671 emerging adults (46.8% women) aged 18–29 years (M = 22.56; SD = 3.04). Results showed that cybervictimization and cyberaggression exhibited the strongest …

Towards Promoting Innovation In Inclusive Education: Behavioural Intention Of Teachers Towards Adopting Ai To Teach Students With Learning Disabilities In The Uae, Fatima Zraydi, Maxwell Peprah Opoku, Bernadette M. Guirguis, Laurent Gabriel Ndijuye, Ebenezer Mensah Gyimah

All Works

The integration of artificial intelligence (AI) in education offers significant potential for identifying and supporting all students, including those with learning difficulties. Although discussions on the potential of AI to advance the learning of students are ongoing, AI usage among teachers to leverage it in the teaching of students with learning disabilities in nonwestern contexts, such as the United Arab Emirates, is unresearched. The study was guided by a unified theory of acceptance and use of technology to examine teachers’ intentions toward adopting AI tools to enhance educational outcomes for students with learning disabilities in the UAE. Using a quantitative …

Image And Metadata-Driven Personality Inference For Career Recommendation: A Social Media-Based Ai Framework For Adolescents, Heba Ismail, Maryam Alhefeiti, Ashraf Khalil

All Works

This study presents a novel AI-based framework that leverages Instagram image and metadata analysis to infer Big Five personality traits and deliver personalized career recommendations for high school students in the UAE. Addressing the limitations of traditional recommender systems that rely on self-reported questionnaires or text, the proposed approach uses multimodal visual features—including profile metrics, HSV color patterns, semantic image labels, and texture analysis—to enable a non-intrusive, scalable personalization method. A pilot study involving data from 30 student accounts served as a proof of concept. Correlation analysis identified profile and HSV features as the most predictive, and four machine learning …

A Data-Driven Koopman Framework For Station-Keeping On Near Rectilinear Halo Orbit, Anusha Sharma Malladi

Theses and Dissertations

Cislunar missions have gained significant attention in recent decades, motivating the need for efficient modeling and reliable control. In this work a Koopman operator based framework is developed for approximating the error dynamics around a reference Near Rectilinear Halo Orbit (NRHO) in the Earth-Moon Circular Restricted Three-Body Problem (CR3BP). A decoder free neural network is used to learn a lifted linear representation of the nonlinear CR3BP dynamics and a residual based approach is used to identify the corresponding control input matrix. The model is then implemented in a receding-horizon target point controller and compared with uncontrolled propagation and a State …

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

Evaluation Of A No-Code Ai Model For Detecting Periapical Radiolucencies: Impact Of Anatomical Region On Diagnostic Performance, Manal Hamdan, Kevin W. Yu, Marguerite Miller, Stephanie J. Sidow, Zaid Badr, Sergio E. Uribe

School of Dentistry Faculty Research and Publications

Background

To develop a no-code artificial intelligence (AI) model for the detection of apical radiolucent lesions and to assess how lesion location influences the model’s diagnostic performance.

Methods

312 periapical radiographs were retrospectively collected, each accompanied by a corresponding cone-beam computed tomography (CBCT) scan obtained within six months and a radiology report authored by board-certified oral and maxillofacial radiologists. These reports served as the reference standard, and all findings were cross-verified by the primary investigator through CBCT review. The dataset included 181 images with at least one apical radiolucent lesion and 131 lesion-free controls. Using the no-code AI platform LandingLens …

Acute Management Of Hydropneumothorax Secondary To Esophageal Perforation After Laparoscopic Fundoplication, Chenxi Shi, Yu Wei Chang, Leah Joyner

Student Publications

Background: Laparoscopic fundoplication is commonly performed for refractory gastroesophageal reflux disease and symptomatic hiatal hernia, but rare postoperative complications such as esophageal perforation may result in significant morbidity and mortality if not promptly recognized.

Case report: We present a case of esophageal perforation complicated by massive hydropneumothorax in a woman who presented to the emergency department with progressive chest pain, abdominal pain, and respiratory distress two weeks after hiatal hernia repair with Nissen fundoplication. Emergent tube thoracostomy performed in the emergency department drained a large volume of purulent fluid and resulted in immediate respiratory improvement. Computed tomography with oral contrast …

Gender Gap In Returns To Publications, Piotr Śpiewanowski, Ivan Stetsyuk, Oleksandr Talavera

All Works

Gender equity in science depends not only on who participates in research, but also on how their work is rewarded. We examine gender gaps in monetary returns to research productivity, pay, and credit attribution using a novel dataset linking salary and publication records for professors at U.S. public universities. While our main contribution shows that there is no robust evidence of a significant gender gap in monetary returns to publications, we uncover substantial heterogeneity across disciplines and authorship structures. Women in medical and health sciences experience a negative gap in returns of 10.7% relative to men for equivalent research output. …

Anticipatory Governance And Leadership For Ai Implementation In Higher Education: A Scoping Review, Sandra Baroudi

All Works

As the education sector attempts to address rapid changes caused by Artificial Intelligence (AI), it becomes crucial to examine approaches to leadership at the organizational and system levels. This scoping review explores how anticipatory models of governance are conceptualised and operationalised globally within higher education settings in the context of AI-related transformations. Using a scoping review design, academic and grey literature published between 2020 and 2025 was searched across Scopus, EBSCOhost, ERIC, Google Scholar, and ProQuest. Nineteen sources were selected based on clear inclusion and exclusion criteria and analysed thematically. Findings revealed that while AI offers promising opportunities to transform …

Engineering Sulfur Concrete Mixes: A Data-Driven Approach To Aggregate Packing And Binder Efficiency, Vasilia Al Khaldi, Abdel Hamid I. Mourad, Maisa El Gamal

All Works

Processing window (mass loss < 3%). A first-order, order-of-magnitude carbon-footprint estimate—presented with explicit caveats rather than as a full life-cycle assessment—indicates that replacing Portland cement with by-product sulfur is the dominant contributor to a substantial reduction in embodied CO₂ per cubic metre relative to equivalent-strength Portland cement concrete. The valorization of steelmaking by-products aligns with circular economy principles, enabling high-performance, recyclable, and low-carbon construction materials without chemical binder modification.

Autonomous Smart Vertical Farming: A Systems-Level Synthesis Of Iot And Solar Energy Integration For Sustainable Agriculture, Mahmuda Khatun Mishu, Md Rokonuzzaman, Boon Kar Yap, Tofan Agung Eka Prasetya, Md Arif Hossain, Asif Islam, Kazi Sajedur Rahman, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

Rapid urbanization, land degradation, and climate variability are increasingly constraining food production, especially in densely populated urban regions. Vertical farming (VF), which grows crops in stacked layers under controlled conditions, is gaining recognition as a potential solution for sustainable urban agriculture. However, high energy requirements and questions surrounding long-term resource efficiency continue to challenge its scalability and environmental viability. This review explores the potential of smart vertical farming (SVF) systems, enhanced by the Internet of Things (IoT), wireless sensor networks (WSNs), and hybrid green energy-harvesting systems such as photovoltaic (PV) and thermoelectric (TE) technologies. This research analyzes how real-time data-driven …

Cardiovascular Disease And Fracture Risk In People With Type 2 Diabetes: A Nationwide Matched Case–Control Study, Aksayan Arunanthy Mahalingasivam, Annika Vestergaard Kvist, Joop P. Van Den Bergh, Cassandra Smith, Joshua R. Lewis, Peter Vestergaard, Nicklas Højgaard Hessellund Rasmussen

Research outputs 2022 to 2026

To examine, among people with type 2 diabetes (T2D), whether cardiovascular disease (CVD) phenotypes and cardiovascular medications are associated with any fracture as the primary outcome and major osteoporotic fracture (MOF) as a secondary outcome. Nationwide registry-based matched case–control study in Denmark (2013–2021) among people with T2D. Cases were individuals with T2D who sustained an incident fracture (n = 12,390), and controls were fracture-free individuals with T2D matched 1:3 by age, sex, T2D onset date, and weighted Charlson Comorbidity Index (n = 37,170). The exposures were overall CVD, prespecified clinical CVD phenotypes (acute myocardial infarction (AMI), stroke, heart failure, atrial …

Coastal Land Uplift And Intensified Land-Use Influence Seagrass Carbon And Nitrogen Sink Capacity Over Millennial Timescales, Martin Dahl, Sara Braun, Maria E. Asplund, Mats Björk, Joeri Kaal, Hans W. Linderholm, Elinor Andrén, Thomas Andrén, Žilvinas Ežerinskis, Madhavu Vidya Faizal, Sara C. Forsberg, Andrius Garbaras, Malin E. Kylander, Pere Masqué, Miguel A. Mateo, Justina Šapolaitė, Oscar Serrano, J. Robin Svensson, Olena Vinogradova, Martin Gullström

Research outputs 2022 to 2026

Seagrass meadows store sedimentary carbon and nitrogen and thus play an important role in climate change mitigation and nutrient retention globally. Here we reconstruct the impact of land-use and coastal land uplift on millennial–scale seagrass (Zostera marina) blue carbon and nitrogen accumulation in the Baltic Sea based on a multiproxy paleoreconstruction approach. We show that increased landscape clearance resulted in higher terrestrial runoff and increased accumulation of carbon and nitrogen, whereas land uplift led to hydrodynamically sheltered environments facilitating seagrass colonization, occurring 1700 and > 4000 years ago. The establishment of the seagrass meadows resulted in enhancement of the quality of …

Cxcr3 Is Associated With T-Cell-Induced Heart Damage In Acute Rheumatic Fever, Francis M. Middleton, Reuben Mcgregor, Natalie Lorenz, Sarah Kilian, Anna E.S. Brooks, Saem Mul Park, Ciara Ramiah, Judith Tresidder, Timothy C. Barnett, Michael Serralha, William J. Martin, Florina Chan Mow, Glenn Pearson, Mark Mayo, David I. Broadhurst, Julie Bennett, Johann Brink, Nigel J. Wilson, Anna P. Ralph, Rachel H. Webb, P. Rod Dunbar, Jonathan Carapetis, Nicole J. Moreland

Research outputs 2022 to 2026

The pathogenesis of acute rheumatic fever (ARF) is poorly understood, limiting the development of immune-modulating therapies to treat disease and prevent progressive heart damage. Here, participants with definite ARF were compared to other severe acute paediatric conditions and matched healthy controls by profiling circulating immune molecules and cells to inform disease mechanisms and potential druggable pathways. ARF shared immunological similarities with other inflammatory conditions, including elevated serum IL-6 and an increased frequency of circulating CD4⁺ T cells. However, elevation of the chemokine CCL5 and immunoglobulin IgG3, along with reduced expression of the chemokine receptor CXCR3 in the T cell …

Genetic Drivers Of Progression In Alzheimer’S Disease Are Distinct From Disease Risk, Celeste E. Cohen, Shane Fernandez, Umran Yaman, Ahmad R. Ehyaei, Eleftheria Kodosaki, Aydan Askarova, Tenielle Porter, Eleanor O’Brien, Paul Maruff, Alexi Nott, John A. Hardy, Simon M. Laws, Dervis A. Salih, Maryam Shoai

Research outputs 2022 to 2026

Background: Recent trials in Alzheimer’s disease (AD) demonstrate encouraging outcomes. These trials target risk mechanisms identified through genetic analysis whilst directly aiming to reduce progression rates. Evidence from other neurodegenerative diseases suggests the genetics of progression is distinct from risk of disease. To expand these initial successes and improve clinical outcomes further we need to understand genetics of progression of disease. These can be deduced through rigorous analysis of meticulously phenotyped longitudinal cohorts. In this study we first looked at known genetic drivers of risk, namely polygenic risk scores for AD and APOE‑ε4, to assess their role in progression. This …