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Articles 80521 - 80550 of 1740722

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An Efficient Diffusion-Based Non-Autoregressive Solver For Traveling Salesman Problem, Mingzhao Wang, You Zhou, Zhiguang Cao, Yubin Xiao, Xuan Wu, Wei Pang, Yuan Jiang, Hui Yang, Peng Zhao, Yuanshu Li Jul 2025

An Efficient Diffusion-Based Non-Autoregressive Solver For Traveling Salesman Problem, Mingzhao Wang, You Zhou, Zhiguang Cao, Yubin Xiao, Xuan Wu, Wei Pang, Yuan Jiang, Hui Yang, Peng Zhao, Yuanshu Li

Research Collection School Of Computing and Information Systems

Recent advances in neural models have shown considerable promise in solving Traveling Salesman Problems (TSPs) without relying on much hand-crafted engineering. However, while non-autoregressive (NAR) approaches benefit from faster inference through parallelism, they typically deliver solutions of inferior quality compared to autoregressive ones. To enhance the solution quality while maintaining fast inference, we propose DEITSP, a diffusion model with efficient iterations tailored for TSP that operates in a NAR manner. Firstly, we introduce a one-step diffusion model that integrates the controlled discrete noise addition process with self-consistency enhancement, enabling optimal solution prediction through simultaneous denoising of multiple solutions. Secondly, we …

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Milpbench: A Large-Scale Benchmark Test Suite For Mixed Integer Linear Programming Problems, Huigen Ye, Yaoyang Cheng, Hua Xu, Zhiguang Cao, Hanzhang Qin Jul 2025

Milpbench: A Large-Scale Benchmark Test Suite For Mixed Integer Linear Programming Problems, Huigen Ye, Yaoyang Cheng, Hua Xu, Zhiguang Cao, Hanzhang Qin

Research Collection School Of Computing and Information Systems

Mixed-integer linear programming (MILP) is a cornerstone of optimization with applications across numerous domains. However, the development and evaluation of MILP-solving algorithms are hindered by existing benchmark datasets, which are often limited in scale, lack diversity, and are poorly structured, making them inadequate for systematic testing across different solving approaches, especially for machine learning (ML)-based methods. To address these issues, we introduce MILPBench, a large-scale benchmark suite comprising 100,000 MILP instances organized into 60 well-categorized classes. Using structural properties and embedding similarity metrics, we developed a novel classification framework to ensure both intra-class homogeneity and inter-class diversity. In addition to …

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Collaboration With Dynamic Open Ad Hoc Team Via Team State Modelling, Jing Sun, Cong Zhang, Zhiguang Cao Jul 2025

Collaboration With Dynamic Open Ad Hoc Team Via Team State Modelling, Jing Sun, Cong Zhang, Zhiguang Cao

Research Collection School Of Computing and Information Systems

Open ad hoc teamwork presents the challenging problem of designing an autonomous agent that can rapidly adapt to collaborate with teammates without prior coordination in an open environment. Existing methods primarily rely on fixed, predefined teammate types, overlooking the fact that teammates may change dynamically. To address this limitation, we propose a novel reinforcement learning approach, the Open Online Teammate Adaptation Framework (Open-OTAF), which enables a controlled agent to collaborate with dynamic teammates in open ad hoc environments. To achieve this, the controlled agent employs a dual teamwork situation inference model to capture the current teamwork state, facilitating decision-making under …

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A Mixed-Curvature Based Pre-Training Paradigm For Multi-Task Vehicle Routing Solver, Suyu Liu, Zhiguang Cao, Shanshan Feng, Yew-Soon Ong Jul 2025

A Mixed-Curvature Based Pre-Training Paradigm For Multi-Task Vehicle Routing Solver, Suyu Liu, Zhiguang Cao, Shanshan Feng, Yew-Soon Ong

Research Collection School Of Computing and Information Systems

Solving various types of vehicle routing problems (VRPs) using a unified neural solver has garnered significant attentions in recent years. Despite their effectiveness, existing neural multi-task solvers often fail to account for the geometric structures inherent in different tasks, which may result in suboptimal performance. To address this limitation, we propose a curvature-aware pre-training framework. Specifically, we leverage mixed-curvature spaces during the feature fusion stage, encouraging the model to capture the underlying geometric properties of each instance. Through extensive experiments, we evaluate the proposed pre-training strategy on existing neural multi-task solvers across a variety of testing scenarios. The results demonstrate …

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Empowering Weight Loss: A Pragmatic Randomized Controlled Trial Of A Theory-Driven Self-Regulation Mobile App For Young Adults With Excess Body Weight, H. S. J. Chew, J. W. Ngooi, R. C. Du, P. Z. Chan, M. Jansson, B. Zhu, Y. Cao, Chong-Wah Ngo, R. Foo, A. Shabbir, D. Ho, N. Sevdalis, K. Y. Ngiam Jul 2025

Empowering Weight Loss: A Pragmatic Randomized Controlled Trial Of A Theory-Driven Self-Regulation Mobile App For Young Adults With Excess Body Weight, H. S. J. Chew, J. W. Ngooi, R. C. Du, P. Z. Chan, M. Jansson, B. Zhu, Y. Cao, Chong-Wah Ngo, R. Foo, A. Shabbir, D. Ho, N. Sevdalis, K. Y. Ngiam

Research Collection School Of Computing and Information Systems

Background/Introduction: Obesity is projected to affect more than half of the global population by 2035, posing significant health and economic challenges. While lifestyle modification is considered a cornerstone of weight management, its effectiveness often relies on substantial support systems. Purpose: This study aimed to evaluate the effectiveness of a 12-week, standalone Temporal Self-Regulation Theory (TST)-based weight loss mobile application, which integrates self-regulation techniques, food logging, and dietary nudging, in promoting weight loss among young adults with excess body weight. Methods: A two-arm, parallel-group, 1:1 randomized controlled trial was conducted, adhering to the CONSORT-Outcomes 2022 Extension guidelines. Participants completed a face-to-face …

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O-Mapl: Offline Multi-Agent Preference Learning, The Viet Bui, Tien Mai, Hong Thanh Nguyen Jul 2025

O-Mapl: Offline Multi-Agent Preference Learning, The Viet Bui, Tien Mai, Hong Thanh Nguyen

Research Collection School Of Computing and Information Systems

Inferring reward functions from demonstrations is a key challenge in reinforcement learning (RL), particularly in multi-agent RL (MARL). The large joint state-action spaces and intricate inter-agent interactions in MARL make inferring the joint reward function especially challenging. While prior studies in single-agent settings have explored ways to recover reward functions and expert policies from human preference feedback, such studies in MARL remain limited. Existing methods typically combine two separate stages, supervised reward learning, and standard MARL algorithms, leading to unstable training processes. In this work, we exploit the inherent connection between reward functions and Q functions in cooperative MARL to …

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Rustmap: Towards Project-Scale C-To-Rust Migration Via Program Analysis And Llm, Xuemeng Cai, Jiakun Liu, Xiping Huang, Yijun Yu, Haitao Wu, Chunmiao Li, Bo Wang, Imam Nur Bani Yusuf, Lingxiao Jiang Jul 2025

Rustmap: Towards Project-Scale C-To-Rust Migration Via Program Analysis And Llm, Xuemeng Cai, Jiakun Liu, Xiping Huang, Yijun Yu, Haitao Wu, Chunmiao Li, Bo Wang, Imam Nur Bani Yusuf, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

Migrating existing C programs into Rust is increasingly desired, as Rust offers superior memory safety while maintaining C’s high performance. Existing automated translation tools, such as C2Rust, may rely too much on syntactic, template-based translation and generate unsafe Rust code that is hard for human developers to read, maintain, or even compile. More semantic-aware translation that produces safer, idiomatic, and runnable Rust code is much needed. This paper introduces a novel dependency-guided and large language model (LLM)-based C-to-Rust translation approach, RustMap, based on three key ideas: (1) Utilize LLM’s capabilities to produce idiomatic Rust code from given small pieces of …

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Retrieval Augmented Generation For Dynamic Graph Modeling, Yuxia Wu, Lizi Liao, Yuan Fang Jul 2025

Retrieval Augmented Generation For Dynamic Graph Modeling, Yuxia Wu, Lizi Liao, Yuan Fang

Research Collection School Of Computing and Information Systems

Modeling dynamic graphs, such as those found in social networks, recommendation systems, and e-commerce platforms, is crucial for capturing evolving relationships and delivering relevant insights over time. Traditional approaches primarily rely on graph neural networks with temporal components or sequence generation models, which often focus narrowly on the historical context of target nodes. This limitation restricts the ability to adapt to new and emerging patterns in dynamic graphs. To address this challenge, we propose a novel framework, Retrieval-Augmented Generation for Dy namic Graph modeling (RAG4DyG ), which enhances dynamic graph predictions by incorporating contextually and temporally relevant examples from broader …

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Cradle: Empowering Foundation Agents Towards General Computer Control, Weihao Tan, Et. Al. Jul 2025

Cradle: Empowering Foundation Agents Towards General Computer Control, Weihao Tan, Et. Al.

Research Collection School Of Computing and Information Systems

Despite their success in specific scenarios, existing foundation agents still struggle to generalize across various virtual scenarios, mainly due to the dramatically different encapsulations of environments with manually designed observation and action spaces. To handle this issue, we propose the General Computer Control (GCC) setting to restrict foundation agents to interact with software through the most unified and standardized interface, i.e., using screenshots as input and keyboard and mouse actions as output. We introduce Cradle, a modular and flexible LMM-powered framework, as a preliminary attempt towards GCC. Enhanced by six key modules, Information Gathering, Self-Reflection, Task Inference, Skill Curation, Action …

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Quantum Technologies In Decentralisation, Paul Robert Griffin, Rudy Raymond, Tsuyoshi Idé Jul 2025

Quantum Technologies In Decentralisation, Paul Robert Griffin, Rudy Raymond, Tsuyoshi Idé

Research Collection School Of Computing and Information Systems

Quantum technologies, rooted in the manipulation of quantum information, are revolutionizing computing and networking domains. Their impact on blockchains and decentralized systems is twofold. While much attention has been given to the potential of quantum computing to attack blockchains, these advanced technologies also offer avenues for strengthening and optimizing them. This chapter delves into the intricacies of quantum technologies, from the foundational concepts of qubits, quantum gates, and quantum networks to their implications for blockchains. We explore both the vulnerabilities of blockchains in a quantum-dominant era and the promising solutions quantum technologies provide, culminating in a use case examining their …

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Generalization Analysis For Supervised Contrastive Representation Learning Under Non‑Iid Settings, Minh Hieu Nong, Antoine Ledent Jul 2025

Generalization Analysis For Supervised Contrastive Representation Learning Under Non‑Iid Settings, Minh Hieu Nong, Antoine Ledent

Research Collection School Of Computing and Information Systems

Contrastive Representation Learning (CRL) has achieved impressive success in various domains in recent years. Nevertheless, the theoretical understanding of the generalization behavior of CRL has remained limited. Moreover, to the best of our knowledge, the current literature only analyzes generalization bounds under the assumption that the data tuples used for contrastive learning are independently and identically distributed. However, in practice, we are often limited to a fixed pool of reusable labeled data points, making it inevitable to recycle data across tuples to create sufficiently large datasets. Therefore, the tuple-wise independence condition imposed by previous works is invalidated. In this paper, …

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Finir: The 2nd Workshop On Financial Information Retrieval In The Era Of Generative Ai, Fengbin Zhu, Yunshan Ma, Fuli Feng, Chao Wang, Huanbo Luan, Guangnan Ye, Shuo Zhang, Dhagash Mehta, Pingping Chen, Bing Xiang, Tat‑Seng Chua Jul 2025

Finir: The 2nd Workshop On Financial Information Retrieval In The Era Of Generative Ai, Fengbin Zhu, Yunshan Ma, Fuli Feng, Chao Wang, Huanbo Luan, Guangnan Ye, Shuo Zhang, Dhagash Mehta, Pingping Chen, Bing Xiang, Tat‑Seng Chua

Research Collection School Of Computing and Information Systems

Recent advancements in Generative AI, such as Large Language Models (LLMs), have demonstrated remarkable success across various general tasks. Extensive studies have explored leveraging generative models in finance, but significant challenges persist. This half-day workshop explores potential approaches and research directions to address these challenges by equipping generative models with advanced Information Retrieval (IR) models. Specifically, this workshop seeks to provide a platform for discussing innovative ideas that facilitate the advancement of IR technology to enrich generative models in finance from four key perspectives: (i) financial IR techniques (ii) financial IR benchmarking and evaluation (iii) financial systems and agents/assistants (iv) …

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Grokformer: Graph Fourier Kolmogorov‑Arnold Transformers, Guoguo Ai, Guansong Pang, Hezhe Qiao, Yuan Gao, Hui Yan Jul 2025

Grokformer: Graph Fourier Kolmogorov‑Arnold Transformers, Guoguo Ai, Guansong Pang, Hezhe Qiao, Yuan Gao, Hui Yan

Research Collection School Of Computing and Information Systems

Graph Transformers (GTs) have demonstrated remarkable performance in graph representation learning over popular graph neural networks (GNNs). However, self-attention, the core module of GTs, preserves only low-frequency signals in graph features, leading to ineffectiveness in capturing other important signals like high-frequency ones. Some recent GT models help alleviate this issue, but their flexibility and expressiveness are still limited since the filters they learn are fixed on predefined graph spectrum or spectral order. To tackle this challenge, we propose a Graph Fourier Kolmogorov-Arnold Transformer (GrokFormer), a novel GT model that learns highly expressive spectral filters with adaptive graph spectrum and spectral …

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What Are Anomalies In A Network?, Kai Ming Ting, Zhong Zhuang, Guansong Pang, Zongyou Liu, Tianrun Liang, Qiuran Zhao Jul 2025

What Are Anomalies In A Network?, Kai Ming Ting, Zhong Zhuang, Guansong Pang, Zongyou Liu, Tianrun Liang, Qiuran Zhao

Research Collection School Of Computing and Information Systems

This article examines a collection of assumptions used in the current literature on node anomaly detection in a network. The examination raises the question: What are anomalies in a network? Our attempt to answer this question has provided some interesting findings and led to some open questions. This is the first article which formally defines anomalies in a network and introduces the concept of self-verifiability of a detector without ground-truths in a network. They enable existing detectors to be categorized into two types along the line whether they are self-verifiable or not. We suggest a method to evaluate self-verifiable detectors …

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Exploring The Capabilities Of Llms For Code-Change-Related Tasks, Lishui Fan, Jiakun Liu, Zhongxin Liu, David Lo, Xin Xia, Shanping Li Jul 2025

Exploring The Capabilities Of Llms For Code-Change-Related Tasks, Lishui Fan, Jiakun Liu, Zhongxin Liu, David Lo, Xin Xia, Shanping Li

Research Collection School Of Computing and Information Systems

Developers deal with code-change-related tasks daily, e.g., reviewing code. Pre-trained code and code-change-oriented models have been adapted to help developers with such tasks. Recently, large language models (LLMs) have shown their effectiveness in code-related tasks. However, existing LLMs for code focus on general code syntax and semantics rather than the differences between two code versions. Thus, it is an open question how LLMs perform on code-change-related tasks.To answer this question, we conduct an empirical study using 1B parameters LLMs on three code-change-related tasks, i.e., code review generation, commit message generation, and just-in-time comment update, with in-context learning (ICL) and parameter-efficient …

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Explaining Explanations: An Empirical Study Of Explanations In Code Reviews, Ratnadira Widyasari, Ting Zhang, Abir Bouraffa, Walid Maalej, David Lo Jul 2025

Explaining Explanations: An Empirical Study Of Explanations In Code Reviews, Ratnadira Widyasari, Ting Zhang, Abir Bouraffa, Walid Maalej, David Lo

Research Collection School Of Computing and Information Systems

Code reviews are central for software quality assurance. Ideally, reviewers should explain their feedback to enable authors of code changes to understand the feedback and act accordingly. Different developers might need different explanations in different contexts. Therefore, assisting this process first requires understanding the types of explanations reviewers usually provide. The goal of this article is to study the types of explanations used in code reviews and explore the potential of Large Language Models (LLMs), specifically ChatGPT, in generating these specific types. We extracted 793 code review comments from Gerrit and manually labeled them based on whether they contained a …

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How Are We Detecting Inconsistent Method Names? An Empirical Study From Code Review Perspective, Kisub Kim, Xin Zhou, Dongsun Kim, Julia Lawall, Kui Liu, Tegawendé F. Bissyandé, Jacques Klein, Jaekwon Lee, David Lo Jul 2025

How Are We Detecting Inconsistent Method Names? An Empirical Study From Code Review Perspective, Kisub Kim, Xin Zhou, Dongsun Kim, Julia Lawall, Kui Liu, Tegawendé F. Bissyandé, Jacques Klein, Jaekwon Lee, David Lo

Research Collection School Of Computing and Information Systems

Proper naming of methods can make program code easier to understand, and thus enhance software maintainability. Yet, developers may use inconsistent names due to poor communication or a lack of familiarity with conventions within the software development lifecycle. To address this issue, much research effort has been invested into building automatic tools that can check for method name inconsistency and recommend consistent names. However, existing datasets generally do not provide precise details about why a method name was deemed improper and required to be changed. Such information can give useful hints on how to improve the recommendation of adequate method …

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Gouldian Finch Monitoring: Nesting Activity - Goomig Project 2024 To 2025, Biota Environmental Sciences Jul 2025

Gouldian Finch Monitoring: Nesting Activity - Goomig Project 2024 To 2025, Biota Environmental Sciences

Irrigated Agricultural Development in the North

The Goomig Project is an irrigated agricultural development located approximately 30 km north of Kununurra, which involved clearing approximately 9,260 ha of vegetation for agriculture. Approximately 11,470 ha of native vegetation surrounding, or remaining between, the cleared areas has been designated as a buPer area (hereafter, the buPer area) to be managed to protect surrounding conservation reserves and watercourses (Strategen 2014). Gouldian Finch monitoring in the buPer area is required as a condition of project approval and is outlined in the Gouldian Finch Conservation Plan (GFCP; Strategen 2014). Item 7 of the monitoring regime requires “annuaI monitoring of breeding populations, …

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The Unappreciated Role Of Intent In Algorithmic Moderation Of Abusive Content On Social Media, Xinyu Wang, Sai Koneru, Pranav Narayanan Venkit, Brett Frischmann, Sarah Rajtmajer Jul 2025

The Unappreciated Role Of Intent In Algorithmic Moderation Of Abusive Content On Social Media, Xinyu Wang, Sai Koneru, Pranav Narayanan Venkit, Brett Frischmann, Sarah Rajtmajer

Faculty Publications

No abstract provided.

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Unheard Echoes: Undocumented Students’ Success Amidst Challenges At U.S. Higher Education Community Colleges, Elvia Ortiz Segura Jul 2025

Unheard Echoes: Undocumented Students’ Success Amidst Challenges At U.S. Higher Education Community Colleges, Elvia Ortiz Segura

Electronic Theses and Dissertations

This qualitative descriptive study explored the lived experiences of undocumented Latinx students at a southern U.S. community college, identifying support services that assisted students with barriers that emerged in their academic journey. The problem of the study was the complex challenges undocumented students face in higher education and how they are addressed and supported. The research used a qualitative descriptive methodology to magnify student voices and influence institutional policies. Using Bronfenbrenner’s ecological systems theory as the theoretical framework, this study examined how family, culture, policy, and institutional systems influenced undocumented students’ educational journeys. Data were collected through semistructured interviews with …

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Psychological Distress Among Suicide Exposed And Subsequently Bereaved Carers, Myfanwy Maple, Navjot Bhullar, Marie Reid, Sarah Wayland Jul 2025

Psychological Distress Among Suicide Exposed And Subsequently Bereaved Carers, Myfanwy Maple, Navjot Bhullar, Marie Reid, Sarah Wayland

Research outputs 2022 to 2026

People bereaved by suicide are at risk of developing significant mental health issues, including the risk of self-harm. To understand suicide exposure and psychological factors contributing to these adverse outcomes, survey data from 92 participants (Meanage = 53.50 years, SD = 14.5, female = 83.7%) who had provided care to someone who subsequently died by suicide were used. Participants responded to questions relating to suicide exposure, bereavement, suicidal ideation and psychological distress. A hierarchical regression analysis found that the perceived impact of suicide death and one's own suicidal ideation explained 46% variance in psychological distress. Suicide bereaved carers are highly …

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Post-Anthropocene Provocations: Human-Sized Scholars’ Rocks, Cronenbergian Flesh Caves And Zen Garden Design Cues For A Future Proof Re(Image)Ining, Brenton Rossow, Darren Tynan Jul 2025

Post-Anthropocene Provocations: Human-Sized Scholars’ Rocks, Cronenbergian Flesh Caves And Zen Garden Design Cues For A Future Proof Re(Image)Ining, Brenton Rossow, Darren Tynan

Research outputs 2022 to 2026

This research explores concertinaing past, present and future interventional creative and pedagogical practices to address the challenges of the Post-Anthropocene era. We argue that the Post-Anthropocene is marked by biotechnological entanglements, environmental violence and digital overstimulation. The discussions herein critique a hyperattentive achievement society characterised by a scattering of attention, a near-constant screen-mediated stream of digital material and tasks and the commodification of leisure time. Enlisting Byung-Chul Han’s concept of hyperattention and themes and motifs from David Cronenberg’s films, the authors propose “FUTURE PROOF re(image)ining” as a collaborative Cli-Fi narrative concept. The project reimagines objects from an initial art installation …

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Eco-Friendly Additives For Biodegradable Polyesters: Recent Progress In Performance Optimization And Environmental Impact Reduction, Ahmad Fayyazbakhsh, Nima Hajinajaf, Hamed Bakhtiari, Michael Feuchter, Ilaria Improta, Ehsan Salehi, Sara Kamal Shahsavar, Marketa Julinova, Amirehsan Ghasemi, Bita Ghasemi, Reza Afsharnia, Marek Koutný, Young Cheol Chang Jul 2025

Eco-Friendly Additives For Biodegradable Polyesters: Recent Progress In Performance Optimization And Environmental Impact Reduction, Ahmad Fayyazbakhsh, Nima Hajinajaf, Hamed Bakhtiari, Michael Feuchter, Ilaria Improta, Ehsan Salehi, Sara Kamal Shahsavar, Marketa Julinova, Amirehsan Ghasemi, Bita Ghasemi, Reza Afsharnia, Marek Koutný, Young Cheol Chang

Research outputs 2022 to 2026

Biodegradable polymers have emerged as principal alternatives to petroleum-based polymers, which exert a detrimental impact on the environment. Among these, biodegradable polyesters stand out as particularly noteworthy, renowned for their exceptional properties that find application across diverse industries, including food packaging, biomedical devices, and agriculture. This comprehensive analysis delves into the impact of various additives, with a focus on eco-friendly ones, on biodegradable polyesters, as evidenced by recent research endeavors. The additives are systematically categorized to provide a nuanced understanding within distinct industrial contexts. In the exploration of these additives, a meticulous classification is employed, ensuring a focused analysis of …

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Performance Of Interrupted Minichannel Heat Sink Using Various Coolant Fluids, Ernie Mat Tokit, Mohd Zamri Yusoff, Hussein A. Mohammed Jul 2025

Performance Of Interrupted Minichannel Heat Sink Using Various Coolant Fluids, Ernie Mat Tokit, Mohd Zamri Yusoff, Hussein A. Mohammed

Research outputs 2022 to 2026

The advancement in the micro electro mechanical system, MEMS, had been utilized for several years before. This embarked on the compact and high density of power generation for tiny devices. This led to the development of a heat dissipating system for high-power-density devices. Hence, the work intends to simulate the fluid flow performance of interrupted minichannel heat sinks due to the redeveloping and interrupting of the boundary layer merging in previous work that augments the heat dissipation. The study is conducted through numerical work of laminar steady flow, by governing the Navier-Stokes and energy equation. Three interrupted minichannel heat sinks …

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A Perspective Or Review Based Entirely On Low-Quality Evidence Is Simply An Opinion, Matthew S. Tenan, Sophia Nimphius Jul 2025

A Perspective Or Review Based Entirely On Low-Quality Evidence Is Simply An Opinion, Matthew S. Tenan, Sophia Nimphius

Research outputs 2022 to 2026

No abstract provided.

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Breast And Prostate Cancer Survivors’ Understanding Of Risk And Management Of Cardiovascular And Musculoskeletal Side Effects Of Treatment: Findings From Focus Groups, Jack Dalla Via, Chris R. Andrew, Brenton J. Baguley, Nina Stewart, Jonathan M. Hodgson, Joshua R. Lewis, Mandy Stanley, Mary A. Kennedy Jul 2025

Breast And Prostate Cancer Survivors’ Understanding Of Risk And Management Of Cardiovascular And Musculoskeletal Side Effects Of Treatment: Findings From Focus Groups, Jack Dalla Via, Chris R. Andrew, Brenton J. Baguley, Nina Stewart, Jonathan M. Hodgson, Joshua R. Lewis, Mandy Stanley, Mary A. Kennedy

Research outputs 2022 to 2026

Purpose: Survival after a cancer diagnosis is improving, increasing the importance of understanding and managing long-term treatment-related adverse effects. This study aimed to understand breast and prostate cancer survivors’ understanding of how cancer treatment may affect cardiovascular and musculoskeletal health. Methods: Australian breast and prostate cancer survivors treated with therapies with known cardiovascular adverse effects were recruited via a private cancer care provider. Participants completed an online background questionnaire, then participated in a focus group. Focus groups were recorded, transcribed, then analysed using reflexive thematic analysis. Results: In total, 26 cancer survivors (15 breast, 11 prostate; mean age 67 years) …

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A Cross-Sectional Examination Of Missed Infection Control Practices Among Nurses In The Jordanian Hospitals, Muhammad Ahmed Alshyyab, Rania Ali Albsoul, Gerard Fitzgerald, Diana Arabiat Jul 2025

A Cross-Sectional Examination Of Missed Infection Control Practices Among Nurses In The Jordanian Hospitals, Muhammad Ahmed Alshyyab, Rania Ali Albsoul, Gerard Fitzgerald, Diana Arabiat

Research outputs 2022 to 2026

Background: Missed infection control practices may negatively impact quality healthcare and patient safety in acute health care settings. Hence, more research is urgently needed especially in Arab countries. To investigate the elements and reasons of missed infection control activities among nurses in Jordan. The sociodemographic correlates with missed infection control activities were also examined. Methods: A cross sectional design was utilized in this study. A convenience sample of 960 nurses from seven hospitals in the North of Jordan was used. The Missed Nursing Care Infection Prevention and Control (MNCIPC) Survey was employed to collect the data. Data were analyzed using …

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A Comparative Study Of The Pullout Strength Of Geostraps And Geogrids In Reinforced Soil, Kshitij Gaur, Ashutosh Trivedi, Sanjay Kumar Shukla Jul 2025

A Comparative Study Of The Pullout Strength Of Geostraps And Geogrids In Reinforced Soil, Kshitij Gaur, Ashutosh Trivedi, Sanjay Kumar Shukla

Research outputs 2022 to 2026

The sustainable development of geotechnical infrastructure necessitates using durable, efficient, and environmentally resilient reinforcement materials. This study investigates the pullout performance of geostraps to assess their potential as a sustainable alternative to conventional geosynthetics. This study focuses on the pullout performance of geostraps, flexible, polymeric reinforcement materials. There has not been a thorough study of their pullout resistance, which directly affects the stability and durability of reinforced soil structures. Pullout tests were conducted on sandy soil in a controlled environment. The experimental findings from the pullout test were then validated in a numerical model. The model was used to determine …

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Models Of Care For Indigenous Children In Rural And Remote Settings: A Global Scoping Review, Joseph Freeman, Thomas Stubbs, Verity Chadwick, Anita Pickard, Tuguy Esgin, Elizabeth J. Elliott, Alexandra Martiniuk Jul 2025

Models Of Care For Indigenous Children In Rural And Remote Settings: A Global Scoping Review, Joseph Freeman, Thomas Stubbs, Verity Chadwick, Anita Pickard, Tuguy Esgin, Elizabeth J. Elliott, Alexandra Martiniuk

Research outputs 2022 to 2026

Indigenous communities internationally have demonstrated remarkable strength despite significant challenges. Health disparities among Indigenous peoples persist due to historical injustices and ongoing racial discrimination, not inherent vulnerabilities. Disparities are rooted in a legacy of colonisation, systemic exclusion, and socio-economic inequities impacting access to healthcare, education, and employment. Preliminary searches show limited literature on models of care for remote living Indigenous children. This review aimed to identify internationally, effective models of care for Indigenous children in rural and remote areas. A scoping review was conducted, analysing literature on models of care for remote Indigenous children. This study followed the JBI’s Scoping …

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Rural Cancer Survivors' Perceived Delays In Seeking Medical Attention, Diagnosis And Treatment: Findings From A Large Qualitative Study, Alyssa Taglieri-Sclocchi, Ingrid Bindicsova, Susannah K. Ayre, Michael Ireland, Sonja March, Fiona Crawford-Williams, Suzanne Chambers, Jeff Dunn, Belinda C. Goodwin, Elizabeth A. Johnston Jul 2025

Rural Cancer Survivors' Perceived Delays In Seeking Medical Attention, Diagnosis And Treatment: Findings From A Large Qualitative Study, Alyssa Taglieri-Sclocchi, Ingrid Bindicsova, Susannah K. Ayre, Michael Ireland, Sonja March, Fiona Crawford-Williams, Suzanne Chambers, Jeff Dunn, Belinda C. Goodwin, Elizabeth A. Johnston

Research outputs 2022 to 2026

Aims: To investigate rural cancer survivors' self-reported reasons for perceived delays in initial cancer detection and treatment. Methods: Within a cohort study, adult cancer survivors who had travelled > 50 km for cancer care, staying at subsidised accommodation lodges in city centres in Queensland, Australia, were invited to complete a structured interview on perceived delays in: (i) seeking medical attention, (ii) receiving their diagnosis and (iii) commencing treatment. Content analysis was used to map self-reported reasons for perceived delays at each step, which were then categorised based on the perceived source: (i) personal, (ii) healthcare professional, (iii) healthcare system or (iv) …

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