Digital Commons Network^™

Evaluation Of Retrieval-Augmented Generation (Rag) With Gpt-4o For Maxillofacial Prosthodontics Clinical Questions, Vinsensia Launardo, Merve Koseoglu, Lucky Susanto, Michael Kase, Amanda Colebeck, Heidi Huber, Maribeth Krzesinski, Derry Wijaya, Muhammad Ruslin, Alvin Gerard Wee, Heng-Li Huang, Lih-Jyh Fuh, Cortino Sukotjo

Journal of Dental Sciences

Background/purpose: Large language models (LLMs) offer promising education and clinical decision support to help address the global shortage of maxillofacial prosthodontists. To overcome the lack of source traceability in base LLMs, this study evaluated a retrieval-augmented generation (RAG) architecture for answering complex clinical questions.

Materials and methods: An expert panel consisting of five maxillofacial prosthodontists selected 15 high-complexity clinical questions. Responses were generated using base GPT-4o and a naive RAG-GPT-4o model built with domain-specific literatures. Outputs were evaluated across five parameters using a 5-point Likert scale and analyzed via Mann-Whitney U tests.

Results: No statistically significant differences …

Prediction Of Adequate Alveolar Ridge Contours For Dental Implant Placement Using An Artificial Intelligence-Based Algorithm, Hao-Chieh Chang, Shan-Pin Pan, Cheng-Liang Wu, Wei-Chan Hsu, Yi-Chun Weng, Po-Chun Chang

Journal of Dental Sciences

Background/purpose: Accurate prediction of ridge contour following ridge augmentation is an integral part of planning dental implant therapy. This study aimed to develop an artificial intelligence (AI)-based algorithm to predict adequate alveolar ridge contours for accommodating implants based on preoperative cone-beam computed tomography (CBCT) images using a deep learning (DL) approach.

Materials and methods: A total of 96 mandibular CBCT images with minor and major defects were used, virtual implants with adequate ridge contours were added, and a U-Net 2.5D model was used for DL training.

Results: The results revealed that the predicted ridge contours achieved Dice Similarity Coefficients of …

Formulation Modification Of Silver Diamine Fluoride To Improve Clinical Handling And Dentin Tubule Occlusion, Liangyu Chang, Yutzu Wu, Powen Lu, Iwen Chen, Weifang Lee, Chunche Lin, Renjei Chung, Poonam Negi, Naichia Teng, Jenchang Yang

Journal of Dental Sciences

Background/purpose: Silver diamine fluoride (SDF) is clinically effective for treating dentinal hypersensitivity and arresting caries, but its poor clinical handling due to low viscosity remain concerns. This study aimed to enhance the rheological properties of SDF by incorporating sodium carboxymethylcellulose (CMC) to improve its clinical manageability. Materials and methods: A 39.34 wt% SDF solution (TMU-SDF) was prepared via wet processing. Its matrix metalloproteinase (MMP) inhibition was evaluated using a fluorogenic MMP-1 assay, and antibacterial activity was tested via an inhibition zone assay. Biocompatibility was assessed using a modified cytotoxicity-agar diffusion test and a skin sensitization test. Rheological properties, including flow …

Exosomes Derived From Bone Substitute-Induced Gingival Mesenchymal Stem Cells Promote Angiogenesis, Chongyu Shen, Zheng Guan, Rui Chu, Zhengyin Li, Jiangting Lu, Liangkun Xie

Journal of Dental Sciences

Background/purpose: In certain clinical bone grafting scenarios, bone substitutes frequently interface with the adjacent soft tissues. This study aimed to investigate whether deproteinized bovine bone mineral (DBBM) and coralline hydroxyapatite (CHA) induce paracrine responses in human gingival mesenchymal stem cells (GMSCs), thereby altering the pro-angiogenic capacity of their derived exosomes, and to profile specific cargo alterations.

Materials and methods: Exosomes were isolated from GMSCs co-cultured with DBBM (DBBM-G-EXO) or CHA (CHA-G-EXO), while native GMSCs-derived exosomes (G-EXO) were collected as controls. The angiogenic effects of these exosomes on human umbilical vein endothelial cells (HUVEC) were evaluated via cell proliferation, scratch wound …

Silencing The Mir-132/Sirt1 Axis Suppresses Nlrp3 Inflammasome Activation And Myofibroblast Differentiation In Oral Submucous Fibrosis, Ming-Yung Chou, Min Yee Ng, Yi-Wen Liao, Chuan-Hang Yu, Cheng-Chia Yu, Sin-Jia Tseng

Journal of Dental Sciences

Background/purpose

Oral submucous fibrosis (OSF) is a chronic oral potentially malignant disorder characterized by progressive extracellular matrix deposition, myofibroblast activation, oxidative stress, and inflammatory signaling. However, the upstream microRNA-mediated mechanisms linking fibrogenesis and NOD-like receptor family pyrin domain-containing protein 3 (NLRP3) inflammasome activation remain unclear. This study investigated the role of the miR-132/sirtuin 1  (SIRT1) axis in OSF-associated fibrotic and inflammatory responses.

Materials and methods

miR-132 expression was examined in OSF tissues, normal tissues, primary buccal mucosal fibroblasts (BMFs), and fibrotic buccal mucosal fibroblasts (fBMFs) using RNA sequencing and quantitative real-time PCR. Patient-derived fBMFs were transfected with a miR-132 inhibitor …

A Scientometric Study On Research Trends And Characteristics Of Kimura Disease, Zhongjing Lv, Yiming Luo, Wei Liu, Jian Yuan

Journal of Dental Sciences

Background/purpose: Kimura disease (KD) is an idiopathic condition that presents as a chronic, benign inflammatory disorder, typically affecting the head and neck region. The purpose of this study was to analyze the scientometric characteristics and research trends of KD.

Materials and methods: All the papers on KD were comprehensively retrieved from the Scopus database. The years of publication were divided into before 2012 and after 2012 in the analysis of research trends.

Results: There were 925 papers on KD, with total citations of 10,821 and the h index of 47. Eosinophilia, lymphadenopathy, nephrotic syndrome, angiofollicular lymph node hyperplasia, …

Artificial Intelligence In Dentistry: A Cross-Domain Bibliometric Analysis Of Technologies, Functional Applications, And Dental Specialties, Yinghui Yang, Cheng-Chia Yu, Min Yee Ng

Journal of Dental Sciences

Background/purpose: Artificial intelligence is increasingly applied in dentistry across diagnosis, prediction, treatment planning, education, and patient communication. This study aimed to provide a structured cross-domain overview of dental AI research by integrating AI technologies, functional applications, and dental specialties within one bibliometric framework.

Materials and methods: AI-related dental publications from 2016 to 2026 were retrieved from the Web of Science Core Collection. Original and review articles were screened and classified by AI technology, functional application, and dental specialty. Bibliometric mapping, collaboration analysis, keyword co-occurrence, and heatmap-based cross-domain visualization were performed.

Results: A total of 920 publications were included. Publication …

Keratin 18 As A Cytoskeletal Regulator Of Epithelial–Mesenchymal Plasticity And Prognostic Risk In Oral Squamous Cell Carcinoma, Tuan-Yu Kao, Hsuan-Chao Lin, Chien-Wei Lai, Julia Yu-Fong Chang, Feng-Chiao Tsai, Jang-Jaer Lee, Jean-San Chia

Journal of Dental Sciences

Background/purpose: Oral squamous cell carcinoma (OSCC) shows poor survival, and conventional staging does not fully capture biologic aggressiveness. Keratin 18 (KRT18) has been linked to malignant progression in epithelial cancers, but its prognostic and biologic significance in OSCC remains unclear. This study investigated whether KRT18 expression is associated with aggressive invasion patterns and adverse outcomes in OSCC, and whether KRT18 contributes to epithelial–mesenchymal plasticity-related malignant phenotypes.

Materials and methods: Eighty-eight non-irradiated OSCC specimens obtained after primary surgical resection at National Taiwan University Hospital were analyzed by immunohistochemistry. Associations between KRT18 expression and clinicopathological variables were assessed, and survival was evaluated …

Corrigendum To "Human Umbilical Cord Mesenchymal Stem Cells Secretome And Nanoemulsion Propolis Combination Ameliorate Osteoclastogenesis In Lipopolysaccharide-Induced Osteolysis In Hyperglycemia Rats"

Journal of Dental Sciences

No abstract provided.

Synergistic Removal Of Microplastic Fibres: Integrating Chitosan Coagulation In Hybrid Water Pre-Treatment Systems, Jayasuriya Arachchilage Nimesha Thathsarani

Theses: Doctorates and Masters

Microplastic fibres (MPFs) are the most prevalent form of microplastics detected in the influents of water and wastewater treatment plants. Owing to their elongated shape and low density, MPFs frequently evade removal even during tertiary processes such as membrane filtration. Enhancing pretreatment, particularly through cost-effective coagulation-flocculation can reduce the treatment burden on downstream systems. However, conventional inorganic coagulants often necessitate high dosages and can leave residual ions, posing environmental concerns.

As a sustainable alternative, the use of environmentally friendly coagulants such as Chitosan has gained attention for MPF removal. While Chitosan exhibits favourable qualities, its practical application is hindered by …

Integrated Incubators: A Novel Framework For Technology-Based Creative Arts Education, Brad Phelps Nisbet

Theses: Doctorates and Masters

This thesis investigates the development and impact of an educational framework designed to bridge the gap between academia and industry within the media and entertainment sector. It addresses the prevalent "skills mismatch" where graduates often lack the specific technical competencies, foundational knowledge, practical experience, or soft skills required for entry-level positions in a rapidly evolving landscape influenced by advancements like virtual production, real-time VFX, immersive media, and Al. Grounded in both theoretical and practical insights, the framework aims to foster student creativity, technical proficiency, industry readiness, transferable skills, and adaptability, prioritising a transformative, student-centric learning experience.

The research employed a …

Study Of Fire Regimes In Southwestern Australia Using Geospatial Techniques, Ana Do Carmo Carvalho

Theses: Doctorates and Masters

The Northern Jarrah Forest in Southwestern Australia (SWA), part of a global biodiversity hotspot, is home to fire-sensitive tree species such as marri (Corymbia calophylla) and jarrah (Eucalyptus marginata). As climate change intensifies drought and extreme fire events, understanding the drivers of fire severity is increasingly critical. This thesis analyses fire regimes within the Mundaring drinking water catchment to better understand the spatiotemporal complexity of fire severity in relation to fire history and environmental factors.

The thesis commences with a review of three Fire History Databases (FHDs) used in SWA, highlighting significant inconsistencies and data gaps across time and space. …

Development Of Virtual Reality Learning Environments In Science To Engage Secondary Students In Hazardous Activities, Luke Spartalis

Theses: Doctorates and Masters

This research examines the need for change in including hazardous activities in education. As different learning technologies develop, platforms that retain authentic outcomes via virtual reality are needed. The main objective of this research is to examine the inclusion of Virtual Reality Learning Environments (VRLEs) to determine their value in areas that include hazardous conditions. The research considered the ways that VR tools could be optimised to support these activities, as well as considering the challenges of VRLE implementation. The study examined whether VRLE’s allowed for authentic experiences to sufficiently drive an acceptance of VR to complement existing teaching and …

Enhancing Deep Reinforcement Learning With Expert Demonstrations For Mobile Robot Navigation In Unstructured Off-Road Environments, Dulitha Dabare

Theses: Doctorates and Masters

Advancements in the field of Deep Learning has ushered in a boom in autonomous navigation research. Most of the work being conducted in this space, however, has focused on on-road urban navigation scenarios, with unstructured outdoor terrain navigation receiving much more limited attention. Given the wide range of applications that exist for legged and wheeled ground robots in off-road environments in areas such as agriculture, mining and disaster recovery, there is a growing need for research work to improve the navigational capabilities of mobile robots deployed in these challenging environments.

A promising candidate for application to these navigation challenges in …

Patient Experiences Of Receiving Home-Based Immunotherapy Infusions - A Constructivist Grounded Theory Study, Patricia Ann Cook

Theses: Doctorates and Masters

Context: The treatment of cancer and chronic health conditions has been greatly revolutionised via intravenous immunotherapy infusions. Demand, both globally and in Australia, is increasing due to several factors including aging and increased populations, subsequent increases of cancer cases, new immunotherapy indications and increased survival rates.

In Perth, Western Australia, a private service provider commenced delivering a home based immunotherapy infusions model of care as a hospital substitution service provider in 2013 and the service has now been extended across Australia. The safety and efficacy of home-based infusions have been well documented in research, and an increasing number of patients …

Load-Settlement Behaviour Of Tailings Dam Foundation Strengthened Using The Wraparound Geosynthetic Reinforcement Technique, Francis Otieno, Sanjay Kumar Shukla

Research outputs 2022 to 2026

This paper presents a numerical investigation of the load–settlement behaviour of a geosynthetic-reinforced tailings foundation comprised of gold tailings, subjected to the weight of a tailings dam embankment. The study considered varying conditions, including the horizontal and vertical components of the wraparound reinforcement, reinforcement burial depth, and shear strength parameters of the foundation material. A particular focus of this study is to investigate the effect of reinforcement wraparound ends on the settlement behaviour of the foundation using commercially available finite element (FE) software. The reinforcement is a single-layer biaxial woven geotextile, with and without wraparound ends, at varying depths from …

Looking Forward, Reflecting Back: The Promise Of Dispute Resolution To Reform The Criminal Legal System, Cynthia Alkon

Faculty Scholarship

The criminal legal system in the United States is plagued by serious and systemic problems. There have been countless efforts at reform over the last many decades that have included changes in what is a crime, how crimes are punished, how prosecutors do their job, and changes in policing. Yet, despite these efforts, problems such as mass incarceration remain deeply embedded. It is easy to be swept up in pessimism when discussing the criminal legal system. Change is hard, at best incremental, and we seem to be in the beginning of an era of backlash against recent reforms. This is …

Equal Justice & Generative Ai, Milan R. Markovic

Faculty Scholarship

The United States has long suffered from unequal access to justice, with countless low-and middle-income Americans forced to navigate the legal system alone. Recently, prominent judges, lawyers, and scholars have seized on generative AI as a potential corrective. These techno-optimists maintain that ChatGPT and other large language models can demystify the law and address unmet legal needs. Chief Justice John Roberts has proclaimed that AI-based tools "have the welcome potential to smooth out any mismatch between available resources and urgent needs in our court system."

Although AI will be an increasingly important source of legal assistance for underserved populations, the …

Effect Of Traditional And Cluster Set Structures On Bar Path Kinematics During High-Volume Power Clean Training, Tsuyoshi Nagatani, Shayne Vial, Kristina L. Kendall, Paul Comfort, Jiahao Yang, G. Gregory Haff

Research outputs 2022 to 2026

The aim of this study was to examine the effects of traditional (TRAD) and cluster (CLU) set structures on bar path kinematics during a series of high-volume power clean sets, and compare insights gained from discrete versus waveform analysis. Twenty participants completed TRAD or CLU protocols in a randomised, crossover design. Each protocol involved three sets of nine repetitions at 70% of one-repetition maximum. In CLU sets, a 30-second inter-repetition rest was applied. During TRAD sets, peak velocity declined, and significant (p ≤ 0.05) changes were observed in both vertical and horizontal barbell displacement across repetitions, indicating fatigue-related technical alterations. …

Designing And Evaluating Quality Transdisciplinary Work-Integrated Learning: Insights Into Practice, Denise Jackson, Claire Lambert, Sonja Coetzee

Research outputs 2022 to 2026

Higher education’s role in fostering innovation and enacting social change is increasingly important. Transdisciplinary Work-Integrated Learning (TWIL) offers opportunities to prepare students to address societal issues by transcending disciplinary boundaries and collaboratively tackling real-world global challenges. While extensive literature exists on established WIL models, research on the critical aspects of designing, implementing and evaluating impactful TWIL activities remains scarce. This paper draws together insights from 15 TWIL academics across 14 Australian universities, highlighting important design elements such as training for small group collaboration, open-ended projects, design thinking, sustained mentorship and reciprocal partnerships. Emerging challenges related to online delivery, teamwork, scalability, …

Thorium Lung Burdens Of Norm Workers Revisited, Gregory S. Hewson, Martin I. Ralph, Marcus Cattani

Research outputs 2022 to 2026

Historical thorium bioassay data collected from Australian mine workers in the 1990s, including in vivo lung counting and thoron-in-breath (TIB) measurements, were re-evaluated using current dosimetric and biokinetic models. Revised daily thorium intakes from bioassay were compared with previous estimates to assess changes in the dose profile and potential implications for contemporary operations. Reanalysis revealed lower estimates of annual dose, including the number of workers assessed as exceeding 20 mSv. However, it was found that intakes derived from industry personal air sampling (PAS) underestimated intake by up to three-fold. This study determined that sensitive bioassay techniques, such as TIB using …

Harnessing Mono-2-(Methacryloyloxy) Ethyl Succinate Grafting For Robust Micro/Nanoplastic-Resistant Ultrafiltration Membranes, Mohadeseh Najafi, Javad Farahbakhsh, Mitra Golgoli, Michael Johns, Masoumeh Zargar

Research outputs 2022 to 2026

The growing presence of microplastics (MPs) and nanoplastics (NPs) in water systems poses a serious threat to conventional treatment processes, particularly membrane filtration. This study focuses on a surface modification strategy for commercial ultrafiltration (UF) membranes via plasma-induced grafting of mono-2-(methacryloyloxy) ethyl succinate (MMES) to enhance resistance against MP/NPs fouling. The membranes were characterised using advanced analytical techniques, including high-resolution scanning electron microscopy (HRSEM), X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM), confirming successful grafting, increased hydrophilicity, and a more negative surface charge. At optimal conditions of grafting (2 min pretreatment, 0.5 M monomer concentration, and 3 h grafting …

Sparse Gradient Training For Recommender Systems, Yunke Qu, Liang Qu, Tong Chen, Xiangyu Zhao, Jianxin Li, Hongzhi Yin

Research outputs 2022 to 2026

Recommender systems are widely applied in numerous online platforms such as shopping and social media platforms. They typically utilize large embedding tables that map users and items to dense vectors of uniform sizes. As the number of users and items continues to grow, this design leads to significant memory consumption and computational inefficiencies. This challenge is particularly pronounced in scenarios such as federated learning, where model parameters are updated locally on edge devices with limited computational resources before being transmitted to a central server for aggregation. Numerous approaches have been proposed to address this issue, among which embedding pruning methods …

Women In The Australian Mining Industry, Michelle Gander, Fleur Sharafizad, Aglae Hernandez Grande, Heidi Vivian, Mahan Poorhosseinzadeh, Kate Blackwood

Research outputs 2022 to 2026

This report synthesises existing research on women’s participation in the Australian mining industry to identify the structural and cultural factors shaping gender inequality across the sector.

Drawing on research conducted over the past four decades, the report brings together what is currently known about how mining workplaces operate and how organisational practices, work arrangements, and site cultures shape the experiences of women across the sector. While many companies have introduced diversity and inclusion initiatives aimed at improving gender balance, the evidence suggests that challenges persist in areas such as operational roles, leadership pathways, and workplace culture.

Specifically, the report examines …

Energy-Efficient Mixed-Criticality Multicore Systems, Fayyaz Ali, Saud Wasly, Amjad Ali, Shahid Iqbal, Asad Masood Khattak, Bashir Hayat, Shah Khalid

All Works

Balancing energy efficiency with stringent timing guarantees in real-time mixed-criticality systems (MCS) is a key challenge, especially in multicore architectures. This paper introduces a novel energy-aware scheduling framework that integrates dynamic voltage and frequency scaling (DVFS) with a Decreasing-Criticality-Decreasing-Utilization (DCDU) allocation approach. The optimal operating frequencies are obtained at each criticality level; high-criticality tasks are assigned to cores at full operating frequency to maintain timing guarantees, while low-criticality tasks are allocated using worst-case execution times scaled to their optimal frequency. A fixed-priority response-time analysis is used for schedulability in low mode, high mode, and during mode changes. The extensive simulations …

Edge-Aware Ris-Assisted Dynamic Channel Allocation With Lightweight Llm Decision Agent For Interference Mitigation In Low-Altitude Remote Sensing Networks, Safiya Nasser Al-Jaradi, Mohammad Kamrul Hasan, Nabeel Al-Qirim, Shayla Islam, Muhammad Attique Khan, Rashid A. Saeed, Hashim Elshafie, Bishwajeet Kumar Pandey, Khairul Akram Zainol Ariffin

All Works

Low-altitude remote sensing networks are increasingly important for applications, such as environmental monitoring, disaster response, infrastructure inspection, and real-time sensing services. However, when many sensing nodes share limited spectrum resources, severe cochannel interference can degrade communication reliability and delay sensing-data delivery. This challenge becomes more critical in edge-enabled deployments, where control decisions must be made under strict latency, memory, and computational constraints. To address this issue, this article proposes a large language model (LLM)-enhanced edge-aware lightweight reconfigurable intelligent surface (RIS)-assisted dynamic channel allocation (EL-RIS-DCA) framework for interference mitigation in dense low-altitude remote sensing networks. The novelty of the proposed framework …

Lightweight Tinyml-Enhanced Task Offloading In Vanets For Next-Generation Intelligent Transportation Systems, Muhammad Ali, Tariq Qayyum, Asadullah Tariq, Zouheir Trabelsi, Irfan Ud Din, Shabir Ahmed

All Works

Vehicular Ad Hoc Networks (VANETs) face resource constraints, high node mobility, and stringent latency requirements, especially in safety-critical applications such as collision avoidance, path planning, and emergency braking. Task offloading to nearby vehicles or Roadside Units (RSUs) mitigates local computational limits, but dynamic conditions, unreliable nodes, and rapid topology changes complicate dependable node selection. This paper proposes a Tiny Machine Learning (TinyML)-enhanced, credibility-based task offloading framework for real-time decision-making in vehicular networks. RSUs evaluate vehicle reliability through a three-component Credibility Assessment Module: a Task Assignment Component that distributes lightweight test tasks and filters unreliable nodes via TinyML inference; a Verification …

A Preliminary Exploratory Assessment Of Chatgpt To Generating Stride Data Flow Diagrams, Hassan Alsayegh, Mohamed El-Attar

All Works

Threat modeling is a core activity in security-by-design practices, enabling early identification of architectural weaknesses before system implementation. The drawings used during STRIDE analysis are typically Data Flow Diagrams (DFDs), referred to as “STRIDE diagrams” in this paper. STRIDE diagrams provide a visual approach for categorizing security threats; however, constructing accurate STRIDE diagrams require experience and is often time-consuming. Recent advances in Large Language Models (LLMs), such as ChatGPT, raise important questions about their suitability for supporting structured security modeling tasks. This study presents a preliminary exploratory assessment of ChatGPT’s ability to generate, analyse, and iteratively refine STRIDE diagrams from …

Sustainable Paper Production From Date Palm And Reed Leaves Through The Valorization Of Agricultural Waste Products, Imane Belyamani, Alreem Alameri, Jacqueline Soghman

All Works

The environmental consequences of wood-based paper production, including greenhouse gas emissions, have accelerated the search for sustainable alternatives. This study investigates the use of reed and date palm fibers as eco-friendly raw materials for paper production, focusing on starch's influence on their thermal, structural, and mechanical properties. Reed fibers exhibited a higher pulp yield (58.2 %) and lower lignin content (7.8 %) compared to date palm fibers (55.9 % yield, 14.1 % lignin), contributing to papers with smoother textures and greater flexibility. The incorporation of starch into both fiber types resulted in notable performance improvements, though the effects were more …

Conceptualizing A Model For Transforming Academic Search With Retrieval-Augmented Generation, Nikesh Narayanan

All Works

This study conceptualizes the transformative potential of RetrievalAugmented Generation (RAG) in academic research, addressing limitations of traditional search methods reliant on keyword matching, Boolean logic, and metadata analysis. RAG combines precise data retrieval with the generative capabilities of advanced AI models, synthesizing dispersed information into coherent outputs. By bridging retrieval accuracy and contextual generation, RAG offers a framework for providing researchers with comprehensive, nuanced, and up-todate insights tailored to their queries. This article explores the integration of tools like ChatGPT and LangChain to outline a RAGbased system, illustrating its potential to enhance academic discovery by harmonizing natural language processing, semantic …