Digital Commons Network^™

New Insights Into The Beliefs Of Secondary Pre-Service Teachers About Mathematics, Vesife Hatisaru, Olivia Johnston, Julia Collins, Benjamin Rott

Research outputs 2022 to 2026

Teachers’ beliefs about mathematics can shape how they approach teaching, learning, and assessment in mathematics classrooms. This study examined Australian pre-service teachers’ (PSTs’) epistemological beliefs about mathematics. A total of 18 PSTs enrolled in Bachelor of Education and Master of Teaching (secondary mathematics) programs participated in the study by answering prompt questions in an open-ended questionnaire. The participants’ responses were content analyzed by categorizing the views evident in the responses into four pre-defined mathematical orientations: formalism-related, scheme-related, process-related, and application-related. Findings have shown that the dominant beliefs for the participants reflected process- or application- related orientations to mathematics. These findings …

A General Bibliometric And Conceptual Structure Approach To Global Trend On Poverty Research In Islam Using Biblioshiny, Mohd Zaid Mustafar, Mohd Khairul Nizam Mohd Aziz, Dziauddin Sharif, Md Azzaat Ahsanie Lokman, Ashraff Bin Ruslan, Saiyidi Mat Roni

Research outputs 2022 to 2026

This study maps the intellectual landscape of research on poverty in Islam using a structured bibliometric approach with Biblioshiny (Bibliometrix) in RStudio. A Scopus search (TITLE-ABS-KEY “poverty” AND “Islam”) conducted on 1 September 2023 identified 279 English-language journal articles published between 1976 and 2023. The corpus spans 227 sources, 646 authors, and 10,262 cited references, with an annual growth rate of about 5%. Performance and science-mapping analyses reveal two “motor themes”—Islamic finance and healthcare/public health—while spiritually anchored constructs (e.g., maqasid, zakat governance, waqf, spiritual poverty) remain peripheral in co-occurrence and thematic maps. Citation patterns indicate higher field-normalized impact when studies …

Parenting In The Age Of Social Media: The Buffering Effect Of Parental Self-Efficacy On The Relationship Between Parental Social Media Use And Parent Child-Relationship Quality, Celeste Tipple, Cindy Branch-Smith

Research outputs 2022 to 2026

The widespread use of technology in daily life has raised concerns about its potential to disrupt social relationships, particularly within one of the most important human relationships: the parent-child relationship. This study assesses whether parental social media use (measured by a novel parental social media intensity scale) affects the parent-child relationship (measured by the child-parent relationship scale – short form), and whether parental self-efficacy (PSE, measured by the parenting sense of competence scale) moderates this effect. A cross-sectional, online survey study using correlational methods was utilised, with a final sample of 89 parents and caregivers (71.9 % women), averaging 42.6 …

The Moderating Effect Of Dietary Patterns On The Association Of Depression And Anxiety With Cognitive Function, Hilal Salim Said Al Shamsi, Samantha L. Gardener, Hamid R. Sohrabi, Kevin Taddei, Colin L. Masters, Stephanie R. Rainey-Smith, Ralph N. Martins, W. M.A.D.B. Fernando

Research outputs 2022 to 2026

Background and aims: Investigating modifiable risk factors, such as diet, is crucial in understanding their effects on the relationship between Alzheimer's disease (AD)-related cognitive decline and related conditions. This study assesses whether dietary patterns moderate the relationship between symptoms of depression, anxiety, and cognitive function in older adults. Given that biological and psychosocial differences between sexes may influence dietary behaviours, mental health symptoms, and cognitive outcomes, conducting sex-stratified analyses will allow for identification of differential associations. Method: Cross-sectional data from cognitively unimpaired older adults (n = 1174, age ≥60 years) from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were …

A Single Bout Of Resistance Or High-Intensity Interval Training Increases Anti-Cancer Myokines And Suppresses Cancer Cell Growth In Vitro In Survivors Of Breast Cancer, Francesco Bettariga, Dennis R. Taaffe, Cristina Crespo-Garcia, Timothy D. Clay, Mauro De Santi, Giulia Baldelli, Sanjeev Adhikari, Elin S. Gray, Daniel A. Galvão, Robert U. Newton

Research outputs 2022 to 2026

Purpose: Breast cancer is the leading cause of cancer-related death in women, highlighting the need for strategies to mitigate recurrence and mortality. We examined the effects of a single bout of resistance training (RT) versus high-intensity interval training (HIIT) on anti-cancer myokines and in vitro cancer cell suppression. Methods: Thirty-two survivors of breast cancer were randomly allocated to a single bout of RT (n = 16) or HIIT (n = 16). Blood was collected before, immediately post (0P) and 30 min post (30P) exercise. We measured serum levels of decorin, interleukin 6 (IL-6), secreted protein acidic and rich in cysteine …

Compassionate Self-Care For Nurses And Midwives: A Sequential Explanatory Mixed Methods Study, Mary Steen, Shwikar Othman, Jennifer Fereday, Annette Briley, Qunyan Xu, Rachael Vernon

Research outputs 2022 to 2026

Background: Awareness of being kind and compassionate to yourself is often overlooked despite emerging evidence that high levels of self-compassion decrease levels of anxiety and improves well-being. Aim: To explore what being compassionate to yourself means to nurses and midwives and increase knowledge and understanding of how self-compassion may enhance well-being. Methods: Mixed methods study design was utilised to investigate and explore the influence of self-compassion on nurses and midwives' well-being. Phase 1 involved quantitative data collection and analysis. Phase 2 qualitative data were collected to expand on quantitative results. Results: Fifty-four participants responded to a pre-workshop questionnaire, 55 completed …

Discordance Of Small Dense Ldl Cholesterol Beyond Ldl Cholesterol Or Non–Hdl Cholesterol And Carotid Plaque, Jinqi Wang, Xiaoyu Zhao, Yanchen Zhao, Rui Jin, Yunfei Li, Jiahe Wang, Yueruijing Liu, Zhiyuan Wu, Xiuhua Guo, Lixin Tao

Research outputs 2022 to 2026

Background: Different low-density lipoprotein (LDL) particles exhibit distinct proatherogenic properties. Objectives: This study sought to evaluate associations of small dense low-density lipoprotein cholesterol (sdLDL-C), large buoyant low-density lipoprotein cholesterol (lbLDL-C), sdLDL-C/LDL-C ratio, and sdLDL-C/lbLDL-C ratio with carotid plaque (CP) risk in the general population, and to perform discordance analyses to determine which biomarker better reflects CP risk beyond low-density lipoprotein cholesterol (LDL-C) and non–high-density lipoprotein cholesterol (non-HDL-C). Methods: This study enrolled 20,369 participants from Beijing Health Management Cohort. Discordant sdLDL-C, lbLDL-C, or ratio metrics (sdLDL-C/LDL-C and sdLDL-C/lbLDL-C) relative to LDL-C or non-HDL-C, and discordant ratio metrics relative to sdLDL-C, were …

Skilled Migrants' Experiences Of Othering, Alterity And Language Policing, Uma Jogulu, Maggie Mcalinden, Melissa A. Parris, Juliana Mutum

Research outputs 2022 to 2026

The Australian Permanent Migration Program and related settlement services have been critical to Australia's success as a stable, democratic and culturally diverse nation. However, emerging research has revealed that this success may come with a high price for as many as one in four skilled migrants who find themselves employed beneath their level of education, expertise and experience, which we define as underemployment. We designed a study that sought to understand the settlement experiences of 36 Asia-Pacific-skilled migrants working as managers. Incorporating Spivak's concepts of subalternity, othering and alterity as a theoretical framework, our analysis uncovered how migrant identity intersected …

The Role Of Diet In Moderating The Relationship Between Symptoms Of Depression And Brain Amyloid Load, Hilal Salim Said J. Al Shamsi, Samantha L. Gardener, Stephanie R. Rainey-Smith, Hamid R. Sohrabi, Kevin C.M. Taddei, Colin L. Masters, Vincent M. Doré, Christopher L. Rowe, W. M.A.D.Binosha Fernando, Ralph N. Martins

Research outputs 2022 to 2026

Background: Healthy lifestyle factors, including diet, may affect brain amyloid beta (Aβ) load. This study examines dietary patterns as moderators of the relationships among symptoms of depression, anxiety, and brain Aβ load. Method: A cross-sectional study of cognitively unimpaired older adults (n = 524) from the Australian Imaging, Biomarkers, and Lifestyle study assessed dietary patterns, depressive and anxiety symptoms, and brain Aβ load. Moderation and simple slope analyses were conducted. Results: The Dietary Approaches to Stop Hypertension (DASH) diet moderated the relationship between depressive and anxiety symptoms and brain Aβ load. Higher symptoms were associated with greater Aβ load in …

Impact Of Patient Diaries On Children, Families, And Healthcare Professionals In Paediatric Intensive Care Settings: A Scoping Review, Fiona Lynch, Jos M Latour, Ruth Endacott

School of Nursing and Midwifery

OBJECTIVE: The aim of this scoping review was to understand the current landscape, features, and volume of evidence that address the review question: what is the impact of Paediatric Intensive Care Unit (PICU) patient diaries on children, families, and healthcare professionals (HCPs)? To provide context: descriptions of diary models was also provided.

METHOD: The search strategy was structured using the Population, Concept, and Context model to focus the review question. The inclusion criteria were intentionally broad to include all studies published in English from January 2016 until November 2024. The databases CINAHL, Medline, and EMBASE were used to retrieve articles, …

Improving Hiv Pep Patient Follow-Up Appointment And Laboratory Testing In A Telehealth Setting: A Quality Improvement Project, Ralston Lockett

Doctor of Nursing Practice Projects

The ongoing HIV epidemic in the United States highlights the need for innovative prevention strategies, including non-occupational post-exposure prophylaxis (nPEP). This Doctor of Nursing Practice (DNP) project evaluated a telehealth-based intervention aimed at increasing HIV PEP follow-up appointments and laboratory completion rates, while also enhancing provider knowledge. Dual interventions included a patient reminder system and provider education. While provider knowledge significantly improved post-intervention, based on Cohen’s d effect size of 0.62, clinical significance was demonstrated by follow-up appointment rates declining from 44% pre-intervention to 41% post-intervention. Laboratory completion rates also decreased, with 53% of patients completing labs pre-intervention compared to …

The Effect Of Wise Leadership On Sustainable Performance, Haneen Raid Rasheed, Hadeel Kadhm Saeed

Journal of Economics and Administrative Sciences

The research aims to know the impact of wise leadership in its dimensions (Intellectual shrewdness, Spurring action, Moral conduct, and Cultivating humility) in achieving sustainable performance (economic performance, social performance, and environmental performance). The researcher chose the Midland Oil Company as a field for applying the research. The researcher distributed a questionnaire to a purposive sample of (126) managers working within the Midland Oil Company, which included (department managers and division officials). The number of questionnaires valid for analysis was (121) out of (126) distributed questionnaires. The researcher relied on the questionnaire as a primary source for collecting information from …

I See Sick People: Beliefs About Sensory Detection Of Infectious Disease Are Largely Consistent Across Cultures, Joshua M. Ackerman, Theodore Samore, Daniel M. T. Fessler, Norman P. Li, Et Al

Research Collection School of Social Sciences

Identifying cues to contagious disease is critical for effectively tracking and defending against interpersonal infection threats. People hold lay beliefs about the types of sensory information most relevant for identifying whether others are sick with transmissible illnesses. Are these beliefs universal, or do they vary along cultural and ecological dimensions? Participants in 58 countries (N = 19,217) judged how effective, and how likely they were to use, cues involving each of the five major sensory modalities in an imagined social interaction during a flu outbreak. Belief patterns were strongly consistent across countries (sight > audition > touch > smell > taste), suggesting a largely …

International Comparison Of Weather And Emission Predictive Building Control, Christian Hepf, Ben Gottkehaskamp, Clayton Miller, Thomas Auer

Research Collection College of Integrative Studies

Building operational energy alone accounts for 28% of global carbon emissions. A sustainable building operation promises enormous savings, especially under the increasing concern of climate change and the rising trends of the digitalization and electrification of buildings. Intelligent control strategies play a crucial role in building systems and electrical energy grids to reach the EU goal of carbon neutrality in 2050 and to manage the rising availability of regenerative energy. This study aims to prove that one can create energy and emission savings with simple weather and emission predictive control (WEPC). Furthermore, this should prove that the simplicity of this …

Evaluation Of Prerequisite Discrimination Skills For Obtaining Assent From Individuals With Intellectual Disabilities: A Translational Study, Jessica J. Helen Detrick

Dissertations

Assent can be defined as an individual’s affirmative agreement to participate and should be obtained by those who cannot consent (i.e., children and adults deemed as “incapable”) when conducting research or providing services. Federal policies recommend considering age, maturity, and psychological state to determine if a participant can assent. Beyond these considerations, there is little guidance. However, practitioners and researchers still have an ethical obligation to obtain assent. Morris and colleagues (2021) conducted a literature review of assent procedures documented within behavior-analytic journals and found few studies. Of the procedures identified, many would likely be difficult to implement with participants …

Roadside Asset Extraction From Mobile Lidar Point Cloud, Yushin Ahn, Riadh Munjy, Stephen Choi

Mineta Transportation Institute

Mobile LiDAR systems are powerful tools that help us map roads and their surroundings in 3D with great speed and precision. The data provided by these systems support urban planning efforts, digital mapping, transportation infrastructure maintenance, and more. This report presents a comprehensive workflow for roadside asset extraction using Mobile Terrestrial Laser Scanning (MTLS) data, focusing on road lane detection, cross-section slope analysis, and point cloud classification. Roadside asset extraction is the identification and classification of roadside features like signs and poles. The dataset, acquired using a high-resolution mobile LiDAR system, contains over 5.7 billion points (pieces of data) across …

Revised Draft Final Butte Treatment Lagoons (Btl) Groundwater Treatment System Routine Operations, Maintenance, And Monitoring (Om&M) Plan, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Perceived Leadership Behaviors And Workplace Motivation: The Predictive Role Of Generational Cohorts In The U.S. Construction Industry, Leslie D. Klinegardner

Electronic Theses and Dissertations

The purpose of this study was to examine the extent to which perceived leadership behaviors predicted workplace motivation among construction workers across generational cohorts in the Greater Houston, Texas area. Grounded in self-determination theory, the research explored how transformational, transactional, and passive-avoidant leadership behaviors predicted the satisfaction and frustration of psychological needs for autonomy, competence, and relatedness. The analysis also considered whether leadership behaviors and generational cohort served as significant predictors of workplace motivation outcomes. The study followed a quantitative, predictive, cross-sectional design using survey methodology. Data were collected using the Multifactor Leadership Questionnaire (MLQ) and the Basic Psychological Need …

Principal Self-Efficacy: A Qualitative Study, Vance E. Self

Electronic Theses and Dissertations

This qualitative study explored elementary principals’ perspectives on the importance of selfefficacy in relation to management responsibilities, instructional leadership, and moral leadership as they impact student achievement measured by the STAAR in a Central Texas school district. The research addressed the growing challenges principals face in high-accountability environments, focusing on how their beliefs in their leadership abilities affect school performance and student outcomes. The purpose was to examine principals’ views on selfefficacy across three domains and to consider implications for leadership preparation, district support, and policy. The study was grounded in a constructivist paradigm and employed a qualitative case study …

Electronic Health Record Downtime, Grace R. Baldauf

Electronic Theses and Dissertations

Electronic health record (EHR) downtime presents significant challenges to patient safety and care quality in acute care settings, particularly regarding timely medication administration. This project addressed the problem of late or absent medication doses during planned or unplanned EHR downtime. The investigator aimed to evaluate the effectiveness of a structured downtime plan in improving nurses’ ability to administer medications on time during periods of EHR unavailability. The investigator used a quantitative design to implement a downtime plan evaluation paradigm. Data were collected using retrospective chart reviews of medication administration records pre-implementation and postimplementation of the downtime plan. The sample included …

Akma+: Security And Privacy-Enhanced And Standard-Compatible Akma For 5g Communication, Guomin Yang, Guomin Yang, Yingjiu Li, Minming Huang, Zilin Shen, Imtiaz Karim, Ralf Sasse, David Basin, Elisa Bertino, Jian Weng, Hwee Hwa Pang, Deng, Robert H.

Research Collection School Of Computing and Information Systems

The Authentication and Key Management for Applications (AKMA) protocol is a fundamental building block for security and privacy of 5G cellular networks. Therefore, it is critical that the protocol is free of vulnerabilities that can be exploited by attackers. Unfortunately, based on a detailed analysis of AKMA, we show that AKMA has several vulnerabilities that may lead to security and privacy breaches.We define AKMA+, an enhanced protocol for 5G communication that protects against security and privacy breaches while maintaining compatibility with existing standards. AKMA+ includes countermeasures for protecting communication between the user equipment (UE) and application functions (AFs) from attackers, …

Faithfulrag: Fact-Level Conflict Modeling For Context-Faithful Retrieval-Augmented Generation, Qinggang Zhang, Zhishang Xiang, Yilin Xiao, Le Wang, Junhui Li, Xinrun Wang, Jinsong Su

Research Collection School Of Computing and Information Systems

Large language models (LLMs) augmented with retrieval systems have demonstrated significant potential in handling knowledge-intensive tasks. However, these models often struggle with unfaithfulness issues, generating outputs that either ignore the retrieved context or inconsistently blend it with the LLM’s parametric knowledge. This issue is particularly severe in cases of knowledge conflict, where the retrieved context conflicts with the model’s parametric knowledge. While existing faithful RAG approaches enforce strict context adherence through well-designed prompts or modified decoding strategies, our analysis reveals a critical limitation: they achieve faithfulness by forcibly suppressing the model’s parametric knowledge, which undermines the model’s internal knowledge structure …

Debate, Reflect, And Distill: Multi-Agent Feedback With Tree-Structured Preference Optimization For Efficient Language Model Enhancement, Xiaofeng Zhou, Heyan Huang, Lizi Liao

Research Collection School Of Computing and Information Systems

Large Language Models (LLMs) continue to set new standards in knowledge-intensive and complex reasoning tasks, yet their high computational demands limit widespread adoption. While distilling large models into smaller ones offers a sustainable solution, current techniques—such as static knowledge distillation, resource-intensive reinforcement learning from human feedback, or limited self-reflection—struggle to yield substantial and lasting performance gains. In this paper, we present a novel Debate and Reflect (D&R) framework that orchestrates multi-turn debates between smaller models and stronger teacher models, eliciting actionable feedback (e.g., error analysis, corrective strategies) to guide student models. Further, we introduce Tree-structured Direct Preference Optimization (T-DPO) to …

Memotune: A Measure And Moment-Driven Fine-Tuning Framework For Quantized Large Language Models, Yun Zhang, Xue Geng, Lizi Liao, Jintong Sun, Minghe Yu, Ge Yu

Research Collection School Of Computing and Information Systems

Quantizing large language models (LLMs) is essential for reducing memory and computational costs in natural language processing. Existing methods combine quantization with parameter-efficient fine-tuning but often fail to meet practical performance requirements. This paper introduces MeMoTune, a novel fine-tuning framework for quantized LLMs. By employing a measure and moment approach within a low-rank approximation framework in probability measure space, MeMoTune optimizes the objective function for superior fine-tuning results. The update process is further refined through scaled gradient, enhancing convergence efficiency and noise robustness. Experiments on tasks like text generation, summarization, and understanding show MeMoTune significantly outperforms state-of-the-art methods, e.g. fine-tuning …

R2dqg: A Quality Meets Diversity Framework For Question Generation Over Knowledge Bases, Yimeng Ren, Yanhua Yu, Lizi Liao, Yuhu Shang, Kangkang Lu, Mingliang Yan

Research Collection School Of Computing and Information Systems

The task of Knowledge-Based Question Generation (KBQG) involves generating natural language questions from structured knowledge sources, posing unique challenges in balancing linguistic diversity and semantic relevance. Existing models often focus on maximizing surface-level similarity to ground-truth questions, neglecting the need for diverse syntactic forms and leading to semantic drift during generation. To overcome these challenges, we propose Refine-Reinforced Diverse Question Generation (R2DQG), a two-phase framework leveraging a generation-then-refinement paradigm. The Generator first constructs a diverse set of expressive templates using dependency parse tree similarity, capturing a wide range of syntactic patterns and styles. These templates guide the creation of question …

Genwriter: Reducing Gender Cues In Biographies Through Text Rewriting, Shweta Soundararajan, Sarah Jane Delany

Conference papers

Gendered language is the use of words that indicate an individual’s gender. Though useful in certain context, it can reinforce gender stereotypes and introduce bias, particularly in machine learning models used for tasks like occupation classification. When textual content such as biographies contains gender cues, it can influence model predictions, leading to unfair outcomes such as reduced hiring opportunities for women. To address this issue, we propose GenWriter, an approach that integrates Case-Based Reasoning (CBR) with Large Language Models (LLMs) to rewrite biographies in a way that obfuscates gender while preserving semantic content. We evaluate GenWriter by measuring gender bias …

Revolutionizing Alzheimer’S Diagnosis: A Hybrid Deep Learning Approach For Enhanced Mri Analysis, Hassan A. Ahmed, Syed H. Ahmed, Kyle Nash

Business Faculty Publications

Alzheimer’s Disease (AD) is a neurodegenerative disorder that primarily affects the elderly, causing cognitive decline and memory loss. Traditional diagnostic methods, such as neuropsychological tests and cerebrospinal fluid analysis, are invasive and time-consuming. Neuroimaging techniques like MRI and PET provide valuable insights but require manual analysis by specialists. This study proposes a hybrid model combining EfficientNetB0, a deep learning architecture, with Convolutional Neural Networks (CNN) to automate AD detection in MRI scans. The model uses data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset, which includes over 200 MRI scans and clinical information. Our results show that the hybrid model …

Knowledge Boundary Of Large Language Models: A Survey, Moxin Li, Yong Zhao, Wenxuan Zhang, Shuaiyi Li, Wenya Xie, See-Kiong Ng, Tat-Seng Chua, Yang Deng

Research Collection School Of Computing and Information Systems

Although large language models (LLMs) store vast amount of knowledge in their parameters, they still have limitations in the memorization and utilization of certain knowledge, leading to undesired behaviors such as generating untruthful and inaccurate responses. This highlights the critical need to understand the knowledge boundary of LLMs, a concept that remains inadequately defined in existing research. In this survey, we propose a comprehensive definition of the LLM knowledge boundary and introduce a formalized taxonomy categorizing knowledge into four distinct types. Using this foundation, we systematically review the field through three key lenses: the motivation for studying LLM knowledge boundaries, …

Colloquial Singaporean English Style Transfer With Fine-Grained Explainable Control, Jinggui Liang, Dung Vo, Yap Hong Xian, Hai Leong Chieu, Kian Ming A. Chai, Jing Jiang, Lizi Liao

Research Collection School Of Computing and Information Systems

Colloquial Singaporean English (Singlish) is an informal English marked by a unique blend of languages reflecting Singapore’s multicultural identity. Style transfer between Singlish and Standard (formal) English is vital for various applications, yet existing methods often lack explainability and fine-grained control. To fill this gap, we contribute in two key ways. First, we construct a large, high-quality dataset of formal and informal sentences, annotated across six linguistic aspects—Syntax, Lexical Borrowing, Pragmatics, Prosody/Phonology, Emoticons/Punctuation, and Code-Switching—with detailed explanations. Starting with manually annotated cases, we scaled the dataset to 140K with ensured quality. Second, inspired by the “Society of Mind” theory, we …

Gnncontext: Gnn-Based Code Context Prediction For Programming Tasks, Xiaoye Zheng, Zhiyuan Wan, Shun Liu, Kaiwen Yang, David Lo, Xiaohu Yang

Research Collection School Of Computing and Information Systems

A code context model comprises source code elements and their relations relevant to a programming task. The capture and use of code context models in software tools can benefit software development practices, such as code navigation and search. Prior research has explored approaches that leverage either the structural information of code or interaction histories of developers with integrated development environments to automate the construction of code context models. However, these approaches primarily capture shallow syntactic and lexical features of code elements, with limited ability to capture contextual and structural dependencies among neighboring code elements. In this paper, we propose GNNContext, …