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2026

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Sensing-Then-Beamforming: Robust Transmission Design For Ris-Empowered Integrated Sensing And Covert Communication, Xingyu Zhao, Min Li, Ming Min Zhao, Shihao Yan, Min Jian Zhao Jan 2026

Sensing-Then-Beamforming: Robust Transmission Design For Ris-Empowered Integrated Sensing And Covert Communication, Xingyu Zhao, Min Li, Ming Min Zhao, Shihao Yan, Min Jian Zhao

Research outputs 2022 to 2026

Traditional covert communication often relies on the knowledge of the warden's channel state information, which is inherently challenging to obtain due to the non-cooperative nature and potential mobility of the warden. The integration of sensing and communication technology provides a promising solution by enabling the legitimate transmitter to sense and track the warden, thereby enhancing transmission covertness. In this paper, we develop a framework for sensing-then-beamforming in reconfigurable intelligent surface (RIS)-empowered integrated sensing and covert communication (ISACC) systems, where the transmitter (Alice) estimates and tracks the mobile aerial warden's channel using sensing echo signals while simultaneously sending covert information to …

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A Novel Deep Transfer Learning-Based Adaptive Cascade Pi Controller Enhanced By Reinforcement Learning Algorithm And Snake Optimization For Robust Speed Regulation Of Brushless Dc Motors, Seyyed Morteza Ghamari, Asma Aziz Jan 2026

A Novel Deep Transfer Learning-Based Adaptive Cascade Pi Controller Enhanced By Reinforcement Learning Algorithm And Snake Optimization For Robust Speed Regulation Of Brushless Dc Motors, Seyyed Morteza Ghamari, Asma Aziz

Research outputs 2022 to 2026

Brushless DC (BLDC) are common in electric cars, industrial automation, and robotics because of their high efficiency, high torque control, and compact size. Nevertheless, strong speed and current regulation is not easily attained because of system variation, load variations and the shortcomings of traditional fixed-gain proportional-integral (PI) controllers. In this paper, a new snake optimization-assisted deep transfer learning-based reinforcement learning (SOA-DTL-RL)-based adaptive cascade PI controller is proposed that combines transfer learning with fast adaptation, Reinforcement learning with real-time optimization, and snake optimization with optimal initial gain selection to guarantee the robust speed and current regulation in BLDC motors. The proposed …

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Bitcoin Halving: How Effective Is It In Driving Cryptocurrency Market Dynamics?, Nyoman Sri Subawa, Caren Angellina Mimaki, I. Made Oka Mahendra, Made Srinitha Millinia Utami Jan 2026

Bitcoin Halving: How Effective Is It In Driving Cryptocurrency Market Dynamics?, Nyoman Sri Subawa, Caren Angellina Mimaki, I. Made Oka Mahendra, Made Srinitha Millinia Utami

Research outputs 2022 to 2026

Bitcoin halving is a quadrennial event that halves mining rewards and is believed to influence cryptocurrency prices and cryptocurrency market dynamics. This study examines the effect of Bitcoin halving on Cryptocurrency Prices, with Government Regulations, Market Sentiment, and Cryptocurrency Performance as mediating variables. A quantitative research approach was employed, gathering original data via survey instruments from 294 participants within the cryptocurrency community in Bali, which were analyzed using PLS-SEM. The findings indicate that Bitcoin halving exerts a favorable and statistically meaningful influence on Government Regulations, Market Sentiment, Cryptocurrency Performance, and Cryptocurrency Prices. Market Sentiment fully mediates the influence of Government …

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C2p-M: Critical Connection Protection In Multiplex Graphs, Conggai Li, Wei Ni, Ming Ding, Youyang Qu, Jianjun Chen, Wenjie Zhang, Thierry Rakotoarivelo Jan 2026

C2p-M: Critical Connection Protection In Multiplex Graphs, Conggai Li, Wei Ni, Ming Ding, Youyang Qu, Jianjun Chen, Wenjie Zhang, Thierry Rakotoarivelo

Research outputs 2022 to 2026

Multiplex graphs represent diverse real-world interactions among entities, where multiple relationship types coexist within the same set of entities. These graphs introduce privacy risks, as data collectors can exploit cross-layer dependencies to infer hidden and sensitive connections. In this work, we propose a C2P-M framework that identifies and protects critical connections while preserving the structural information in multiplex graphs. Unlike conventional methods for single-layer graphs that perturb all edges uniformly, C2P-M selectively protects critical connections, maintaining the analytical usability of the graph. To achieve this, we introduce the multiplex p-cohesion model, which incorporates new score functions that account for both …

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Effect Of Caffeine Ingestion On Cycling Performance: A Systematic Review And Meta-Analysis, Jinyan Wu, Kai Xu, Mingyue Yin, Xianming Ding, Tong Wang, Qiubo Zhang, Xiaowei Wu, Ningkun Xiao Jan 2026

Effect Of Caffeine Ingestion On Cycling Performance: A Systematic Review And Meta-Analysis, Jinyan Wu, Kai Xu, Mingyue Yin, Xianming Ding, Tong Wang, Qiubo Zhang, Xiaowei Wu, Ningkun Xiao

Research outputs 2022 to 2026

This study aimed to determine the effects of acute caffeine ingestion on cycling performance through a systematic review and meta-analysis, while also exploring the moderating roles of caffeine dosage, training status, and athlete age. A comprehensive search was conducted across five databases, yielding 20 eligible studies with a total of 226 participants. A three-level mixed-effects model was applied to pool main effects on cycling time trial performance, mean power output, mean heart rate, and ratings of perceived exertion (RPE). Subgroup analyses and meta-regression were performed to examine potential moderators. Caffeine intake significantly reduced cycling completion time (SMD = −0.36, 95% …

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Effects Of Electroshock Treatment On Microstructure Evolution And Mechanical Properties Of Ti-8al-1mo-1v Alloy, Jian Zhou, Yu Peng Yao, Hong Xin Sun, Chang Liu, Yan Wen, Li Qiang Wang, Lai Chang Zhang, Le Chun Xie, Lin Hua Jan 2026

Effects Of Electroshock Treatment On Microstructure Evolution And Mechanical Properties Of Ti-8al-1mo-1v Alloy, Jian Zhou, Yu Peng Yao, Hong Xin Sun, Chang Liu, Yan Wen, Li Qiang Wang, Lai Chang Zhang, Le Chun Xie, Lin Hua

Research outputs 2022 to 2026

The effect mechanism of electroshock treatment (EST) on microstructure evolution and mechanical property variations of Ti-8Al-1Mo-1V alloy was investigated. The results show that EST results in the phase transformation from the acicular secondary αs to β phase. While the EST time is 0.12 s, the acicular martensitic phase (αM) precipitates. The results of electron backscattered diffraction (EBSD) reveals that the average grain size decreases from 3.95 to 2.53 μm after EST, indicating that the grains are refined, and the significant recrystallization behavior and martensitic transformation occur. The orientation distribution reveals a more uniform distribution of texture, which is caused by …

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Glycomedicine: Unveiling The Paracentral Dogma, Wei Wang, Gordan Lauc Jan 2026

Glycomedicine: Unveiling The Paracentral Dogma, Wei Wang, Gordan Lauc

Research outputs 2022 to 2026

No abstract provided.

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Optimizing Ev Battery Charging Using Fuzzy Logic In The Presence Of Uncertainties And Unknown Parameters, Minhaz Uddin Ahmed, Md Ohirul Qays, Stefan Lachowicz, Parvez Mahmud Jan 2026

Optimizing Ev Battery Charging Using Fuzzy Logic In The Presence Of Uncertainties And Unknown Parameters, Minhaz Uddin Ahmed, Md Ohirul Qays, Stefan Lachowicz, Parvez Mahmud

Research outputs 2022 to 2026

The growing use of electric vehicles (EVs) creates challenges in designing charging systems that are smart, dependable, and efficient, especially when environmental conditions change. This research proposes a fuzzy-logic-based PID control strategy integrated into a photovoltaic (PV) powered EV charging system to address uncertainties such as fluctuating solar irradiance, grid instability, and dynamic load demands. A MATLAB-R2023a/Simulink-R2023a model was developed to simulate the charging process using real-time adaptive control. The fuzzy logic controller (FLC) automatically updates the PID gains by evaluating the error and how quickly the error is changing. This adaptive approach enables efficient voltage regulation and improved system …

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Prevalence Of Dementia In Selected Middle East And North Africa (Mena) Countries: A Systematic Review And Meta-Analysis, Mohsen Sedighi, Mohammad Hasan Shahabi, Alireza Amanollahi, Khurshid Alam, Soudabeh Shemehsavar, Zahra Shirzadi, Serena Sabatini, Ahmad R. Khatoonabadi, Matthew Prina, Akram A. Hosseini, Claire V. Burley, Jennifer Dunne, Simin Mahinrad, Iman Dajani, Ralph N. Martins, Blossom C.M. Stephan, Ali Chaari, Hamid R. Sohrabi Jan 2026

Prevalence Of Dementia In Selected Middle East And North Africa (Mena) Countries: A Systematic Review And Meta-Analysis, Mohsen Sedighi, Mohammad Hasan Shahabi, Alireza Amanollahi, Khurshid Alam, Soudabeh Shemehsavar, Zahra Shirzadi, Serena Sabatini, Ahmad R. Khatoonabadi, Matthew Prina, Akram A. Hosseini, Claire V. Burley, Jennifer Dunne, Simin Mahinrad, Iman Dajani, Ralph N. Martins, Blossom C.M. Stephan, Ali Chaari, Hamid R. Sohrabi

Research outputs 2022 to 2026

Data on dementia epidemiology in the Middle East and North Africa (MENA) region is limited. This systematic review and meta-analysis examined dementia prevalence across MENA. Databases were searched up to October 2024. Analyses were stratified by country and sex. Pooled prevalence was estimated using a random-effects model with a 95% confidence interval (CI). Fifty-two studies on the selected countries met inclusion criteria, covering 87,219 individuals with dementia from a total population of 1,045,908. The pooled prevalence was 12.16% (95% CI: 9.61–14.96) for the region and the Israel had the highest prevalence (17.00%), followed by Iran (13.20%), Turkey (11.40%), Saudi Arabia …

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Rapid Decentralized Prostate Cancer Risk Stratification By Portable Liquid Biopsy Analysis Within A Clinical Biosensor Validation Framework, Kevin M. Koo, Grant Phillips, Sriganesh Srihari, Áine Farrell, Binny Jaradi, Kira J. Fitzpatrick, John W. Yaxley, Hemamali Samaratunga, Paul N. Mainwaring, Ke-Lin Ru, Darren J. Korbie, Scott A. Tomlins, Matthew J. Roberts, Robert A. Gardiner, Matt Trau Jan 2026

Rapid Decentralized Prostate Cancer Risk Stratification By Portable Liquid Biopsy Analysis Within A Clinical Biosensor Validation Framework, Kevin M. Koo, Grant Phillips, Sriganesh Srihari, Áine Farrell, Binny Jaradi, Kira J. Fitzpatrick, John W. Yaxley, Hemamali Samaratunga, Paul N. Mainwaring, Ke-Lin Ru, Darren J. Korbie, Scott A. Tomlins, Matthew J. Roberts, Robert A. Gardiner, Matt Trau

Research outputs 2022 to 2026

Clinical liquid biopsy (e.g., blood or urine) specimens, as a minimally invasive source of crucial molecular information, continue to grow in importance for efficacious targeted cancer treatment. Yet, current molecular profiling technologies are still confined to centralized laboratory testing, which escalates testing costs, result turnaround time, and patient anxiety. Crucially, there is also a scarcity of purposeful clinical validation studies to rigorously evaluate emerging liquid biopsy technologies from research settings to facilitate clinical translation. Here, we report liquid biopsy biosensor advancements in achieving rapid, accurate, and decentralized molecular profiling of a clinically accredited prostate cancer (PCa) urinary circulating RNA biomarker …

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Sparse Gradient Training For Recommender Systems, Yunke Qu, Liang Qu, Tong Chen, Xiangyu Zhao, Jianxin Li, Hongzhi Yin Jan 2026

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 …

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The Nature Of Agency: Designing Agentic Systems Using A Biomimetic Lens, Tegwen Malik, Laurie Hughes, Yogesh K. Dwivedi, Natalie De Mello, Igor Barahona, Il Jeon Jan 2026

The Nature Of Agency: Designing Agentic Systems Using A Biomimetic Lens, Tegwen Malik, Laurie Hughes, Yogesh K. Dwivedi, Natalie De Mello, Igor Barahona, Il Jeon

Research outputs 2022 to 2026

Purpose: This paper aims to explore how biomimetic principles can inform governance models for agentic artificial intelligence (AI) systems, autonomous, adaptive entities that challenge traditional oversight frameworks. It argues that nature-inspired governance offers a dynamic alternative to static, compliance-based models. Design/methodology/approach: This study adopts a conceptual viewpoint approach. It synthesizes literature on AI governance, systems theory and biomimicry, applying thematic analysis to existing frameworks and mapping identified gaps to five natural principles: symmetry, fractals, cymatic feedback, self-organization and phase transitions. Findings: Current governance frameworks lack mechanisms for managing emergent behaviors and distributed agency in agentic AI. The proposed biomimetic lens …

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Feeling Giggity: Ambiguous Emojis In Teaching And Learning Communications, Mary Kynn, Nicole Reinke, Eva Hatje Jan 2026

Feeling Giggity: Ambiguous Emojis In Teaching And Learning Communications, Mary Kynn, Nicole Reinke, Eva Hatje

Research outputs 2022 to 2026

There is an increase in the number of digital platforms used in higher education classrooms that promote using emojis to capture students’ emotions. However, there is little evidence to suggest that interpretation of emojis is reliable in this context. This pilot project explored if emojis can reliably signify the emotions expressed by first-year university students. Students were asked to record their emotions by selecting a representative emoji and using free text to describe its meaning. A total of 72 responses were recorded in an anonymous online survey. Happy face emojis were used more frequently than emojis representing neutral or unpleasant …

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Numerically Evaluating The Effect Of Extrusion Angle On Material Flow And Thermal Behaviour During Additive Friction Extrusion Deposition (Afed), Numan Habib, Ferdinando Guzzomi, Ana Vafadar Jan 2026

Numerically Evaluating The Effect Of Extrusion Angle On Material Flow And Thermal Behaviour During Additive Friction Extrusion Deposition (Afed), Numan Habib, Ferdinando Guzzomi, Ana Vafadar

Research outputs 2022 to 2026

Additive Friction Extrusion Deposition (AFED), also known as “SoftTouch”, is an emerging friction-based Additive Manufacturing (AM) technology allowing material to soften before the deposition, increasing the printing speed and reducing cost [1]. However, high power is required during the process, as excessive force is needed to extrude enough material through the printing head. This study investigates how extrusion angle and tool rotational speed affect thermal distribution and material flow in AFED to minimise power consumption. A three-dimensional computational fluid dynamics (CFD) model is proposed, and ANSYS ® Workbench CFD code (Fluent) is used to discretise the CFD model. A User-Defined …

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ℵ-Ipomdp: Mitigating Deception In A Cognitive Hierarchy With Off-Policy Counterfactual Anomaly Detection, Nitay Alon, Joseph M. Barnby, Stefan Sarkadi, Lion Schulz, Jeffrey S. Rosenschein, Peter Dayan Jan 2026

ℵ-Ipomdp: Mitigating Deception In A Cognitive Hierarchy With Off-Policy Counterfactual Anomaly Detection, Nitay Alon, Joseph M. Barnby, Stefan Sarkadi, Lion Schulz, Jeffrey S. Rosenschein, Peter Dayan

Research outputs 2022 to 2026

Social agents with finitely nested opponent models are vulnerable to manipulation by agents with deeper recursive capabilities. This imbalance, rooted in logic and the theory of recursive modelling frameworks, cannot be solved directly. We propose a computational framework called ℵ-IPOMDP, which augments the Bayesian inference of model-based RL agents with an anomaly detection algorithm and an out-of-belief policy. Our mechanism allows agents to realize that they are being deceived, even if they cannot understand how, and to deter opponents via a credible threat. We test this framework in both a mixed-motive and a zero-sum game. Our results demonstrate the ℵ-mechanism’s …

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Research For Ethical Factors Predicting Chatgpt Use, Scott Hannah Jan 2026

Research For Ethical Factors Predicting Chatgpt Use, Scott Hannah

Research Datasets

Although ChatGPT was not designed for therapeutic purposes, it is increasingly being used as an accessible source of informal mental health support. However, there is limited empirical evidence regarding users' ethical concerns about privacy, confidentiality, and advice quality, and whether these concerns influence engagement with Artificial Intelligence (AI) mediated mental health support. Our main aim was to investigate whether these ethical concerns predict ChatGPT usage for mental health support. A sample of 256 individuals, predominantly university students, completed self-report measures to assess intentions to use ChatGPT for mental health support and ethical items related to privacy, confidentiality, preference for human …

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Exploring The Las-Vict Principle Of Cryptocurrency Exchanges: A Belief–Action–Outcome Perspective, Cheuk Hang Au, Kevin K.W. Ho, Po Hsu Shieh, Kris M.Y. Law Jan 2026

Exploring The Las-Vict Principle Of Cryptocurrency Exchanges: A Belief–Action–Outcome Perspective, Cheuk Hang Au, Kevin K.W. Ho, Po Hsu Shieh, Kris M.Y. Law

Research outputs 2022 to 2026

Purpose – Cryptocurrency exchanges operate in a hyper-volatile, “wild west” environment, fundamentally challenging existing theories of FinTech success that were built for stable markets. The literature lacks a framework to explain how firms thrive amidst such extreme regulatory ambiguity and institutional distrust. This study resolves this theoretical puzzle by developing a new principle for success in nascent, high-stakes digital ecosystems. Design/methodology/approach – We conduct a multiple-case study of 14 leading cryptocurrency exchanges. Using the belief–action–outcome (BAO) logic as an analytical guide, we deconstruct the strategic actions that separate successful exchanges from failures, synthesising them into a new, empirically grounded framework. …

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No Screens Before Two: How First-Time Australian Parents Negotiate Enduring Digital Media Guidelines, Stephanie C. Milford, Emma Jayakumar, Harrison W. See, Lelia Green Jan 2026

No Screens Before Two: How First-Time Australian Parents Negotiate Enduring Digital Media Guidelines, Stephanie C. Milford, Emma Jayakumar, Harrison W. See, Lelia Green

Research outputs 2022 to 2026

Digital parenting guidance often fails to reflect early caregiving realities, particularly for first-time parents navigating screentime. Although professional guidelines have shifted from rigid time limits toward co-engagement and content quality, these shifts are inconsistently communicated and poorly absorbed into public discourse. Meanwhile, technopanic narratives fuel confusion, guilt, and social judgement. While some studies link extended screen use with adverse outcomes, we examine how correlational findings become blanket prescriptions in early caregiving. Drawing on two interview rounds and three focus groups with 23 Australian first-time parents of children aged birth-to-four, and informed by a socio-ecological approach, we explore how parents interpret …

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Students’ Perspectives On Authentic Assessment: An Experiential Learning Framework For Work-Readiness And Employability, Claire Lambert, Madeleine Ogilvie, Stephanie Meek Jan 2026

Students’ Perspectives On Authentic Assessment: An Experiential Learning Framework For Work-Readiness And Employability, Claire Lambert, Madeleine Ogilvie, Stephanie Meek

Research outputs 2022 to 2026

Background: Universities are increasingly pressured to enhance graduate employability by embedding career readiness into curricula. Authentic, industry-based assessments offer a means to link theory with practice, yet little is known about their impact from the student perspective. Purpose: This study explored how an industry-based authentic assessment supports students’ transition to work through the lens of Experiential Learning Theory (ELT). Method: Using a qualitative design, guided-introspection questionnaires were completed by 20 marketing graduates 2 years after completing an industry-based social marketing project. Directed content analysis identified themes aligned with ELT stages and mechanisms of confidence, networks, and professional enculturation. Findings: Authentic …

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Super-Resolution Learning Inspired Spectral-Spatial Correlation Network For Hyperspectral Target Detection, Jiaping Zhong, Yunsong Li, Jianxin Li, Yanzi Shi, Weiying Xie, Paolo Gamba Jan 2026

Super-Resolution Learning Inspired Spectral-Spatial Correlation Network For Hyperspectral Target Detection, Jiaping Zhong, Yunsong Li, Jianxin Li, Yanzi Shi, Weiying Xie, Paolo Gamba

Research outputs 2022 to 2026

Hyperspectral target detection (HTD) aims at extracting targets from complex backgrounds while overcoming noise interference. Existing deep learning models for HTD usually suffer from low spatial resolution and unitary representation, especially in space-borne platforms. Super-resolution, as a critical technology to enhance the spatial details, could effectively address the aforementioned issue. To make super-resolution absolutely pose positive effects on target detection, this paper proposes an end-to-end novel super-resolution learning inspired spectral-spatial correlation network for hyperspectral target detection (SR-HTD) from the perspective of spatial and spectral regularization to achieve high-precision detection. Specifically, we designed a Spatial Correlation Aggregation (SCA) module inspired by …

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Additive Manufacturing And Heat Treatment Of Zero Poisson’S Ratio Self-Expanding Nitinol Stents, Farhana Yasmin, Vafadar, Majid Tolouei-Rad Jan 2026

Additive Manufacturing And Heat Treatment Of Zero Poisson’S Ratio Self-Expanding Nitinol Stents, Farhana Yasmin, Vafadar, Majid Tolouei-Rad

Research outputs 2022 to 2026

Additive manufacturing (AM) has recently gained attention as an effective approach for printing patient-specific, self-expanding Nitinol (NiTi alloy) stents with complex structural designs for the treatment of peripheral arterial disease (PAD). However, achieving the desired phase transformation temperature and superelastic performance remains challenging due to compositional variations, phase imbalance and microstructural inhomogeneities introduced during the printing process. In this study, self-expanding Nitinol stents with a zero Poisson’s ratio (ZPR) structural design were fabricated via laser powder bed fusion (PBF-LB). The printed stents showed no evidence of cracks or structural defects, confirming PBF-LB’s capability to produce mechanically sound stent geometries. However, …

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Becoming A Nurse: A Lifelong Journey Beyond The Transition To Professional Practice-An Analytical Discursive Paper, Seung A. Park, Eckert, Rebecca Sharp, Judy Duchscher, Micah D.J. Peters Jan 2026

Becoming A Nurse: A Lifelong Journey Beyond The Transition To Professional Practice-An Analytical Discursive Paper, Seung A. Park, Eckert, Rebecca Sharp, Judy Duchscher, Micah D.J. Peters

Research outputs 2022 to 2026

Aim: To reconceptualise becoming a nurse as a lifelong developmental journey that extends beyond the traditional focus on new graduate transition, and to inform policies and practices supporting recruitment, retention and career sustainability. Background: The global nursing shortage persists, exacerbated by high attrition rates among new graduates and an aging workforce. While existing literature predominantly examines the transition from student to professional practice, we propose that ‘becoming a nurse’ begins earlier and extends beyond clinical roles into retirement. Design: An analytical discursive paper. Data Sources: Key theoretical frameworks (Schlossberg's Transition Model, Kennedy's Integrated Transition Model, Benner's Novice-to-Expert framework and Duchscher's …

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Photocatalytic Degradation Of Cephalexin, Amoxicillin, And Phenol Red Using A Green-Synthesized Folic Acid–Zno–Bi2o3 Nanoporous System, M. Sarani, Haghighi, P. Tamaddon, A. Najafidoust, P. Faghani-Eskandarkolaei, N. Sattarahmady Jan 2026

Photocatalytic Degradation Of Cephalexin, Amoxicillin, And Phenol Red Using A Green-Synthesized Folic Acid–Zno–Bi2o3 Nanoporous System, M. Sarani, Haghighi, P. Tamaddon, A. Najafidoust, P. Faghani-Eskandarkolaei, N. Sattarahmady

Research outputs 2022 to 2026

The persistent presence of pharmaceutical pollutants like amoxicillin (AMX) and cephalexin (CPX), and industrial dyes such as phenol red (PR) in wastewater poses serious ecological and public health risks, including antibiotic resistance. It necessitates efficient and low-cost remediation technologies. Photocatalysts employing innovative and engineered nanomaterials such as bismuth oxide (Bi2O3) and zinc oxide (ZnO) nanostructures exhibit considerable potential for eliminating pollutants. This study focused on the photodegradation of AMX, CPX, and PR utilizing green-synthesized folic acid–ZnO–Bi2O3 nanoparticles (F-Zn-Bi NPs) under visible light irradiation. Characterization of the synthesized photocatalyst was conducted using various techniques of powder x-ray diffraction (PXRD), field emission …

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The Factors Influencing Organisational Responsiveness For Sustainable Projects, Richard Hughes, Bradley Baker Jan 2026

The Factors Influencing Organisational Responsiveness For Sustainable Projects, Richard Hughes, Bradley Baker

Research outputs 2022 to 2026

Purpose: This study investigates how organisations respond to sustainability when it becomes a central strategic priority, particularly through project environments. The research seeks to understand the factors influencing organisational responsiveness to sustainability imperatives in projects, addressing a key gap in sustainable project management literature. Design/methodology/approach: The study employed a thematic meta-synthesis of qualitative case studies from multiple countries and different economic sectors. Using grounded theory, data were coded to identify first-order concepts, second-order themes and aggregate dimensions, culminating in the development of a conceptual model of dynamic adaptation. Findings: The analysis revealed three interrelated dimensions that shape organisational responsiveness: strategic …

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On Burden Of Diseases, Prevention, Medical Research And Health Service Delivery: Grampian Case Study, Seshadri S. Vasan, Sudarshan Anand, Miae Lee, Nicholas C. Fluck Jan 2026

On Burden Of Diseases, Prevention, Medical Research And Health Service Delivery: Grampian Case Study, Seshadri S. Vasan, Sudarshan Anand, Miae Lee, Nicholas C. Fluck

Research outputs 2022 to 2026

Burden of diseases measured as disability-adjusted life years (DALYs) per 100,000 people can be mined from public domain data, when they are made available by population health surveillance systems. This can be analysed to allow insightful comparisons with the national average, and to understand differences in trends between the sexes, age groups, time periods, geographic regions, and sub-regions. In this illustrative case study, we have analysed the Scottish burden of disease database to understand what ailed the population of the Grampian region before the COVID-19 pandemic. We have identified that selected cancers, ischaemic heart disease, Alzheimer’s disease and other dementias …

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Chronic Disease Prevalence And Modifiable Risk Factors Among Undergraduate Students At Ha’Il University: A Population-Level Cross-Sectional Study, Collins Otieno Asweto, Sehar Un Nisa Hassan, Mohamed Ali Alzain, Bandar Alsaif, Mohammed Elshiekh Saeed, Ahmed Kassar, Kamal Elbssir Mohammed Ali, Mouna Ghorbel, Rafat Zrieq, Monzer Hamed, Wei Wang Jan 2026

Chronic Disease Prevalence And Modifiable Risk Factors Among Undergraduate Students At Ha’Il University: A Population-Level Cross-Sectional Study, Collins Otieno Asweto, Sehar Un Nisa Hassan, Mohamed Ali Alzain, Bandar Alsaif, Mohammed Elshiekh Saeed, Ahmed Kassar, Kamal Elbssir Mohammed Ali, Mouna Ghorbel, Rafat Zrieq, Monzer Hamed, Wei Wang

Research outputs 2022 to 2026

Background: Rising rates of chronic conditions among Saudi youth underscore the need for early prevention. Using a public‑health lens focused on demographic, academic, and lifestyle influences, this study investigates the risk and protective factors for chronic disease among students at the University of Ha’il to guide youth‑centered health policies and long‑term wellbeing initiatives. Methods: A cross-sectional survey was conducted among 10,775 undergraduate students studying in bachelor’s degree programs at Ha’il University, Saudi Arabia. Descriptive analyses were used to assess demographic characteristics, academic status, health status, and health-related lifestyles. Multiple logistic regression models were applied to determine which demographic, academic, and …

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How Expert Designers Foster Expertise: A Study Of Professional Visual Communication Practice, Grant Ellmers, Marius Foley, Juliana Peloche Jan 2026

How Expert Designers Foster Expertise: A Study Of Professional Visual Communication Practice, Grant Ellmers, Marius Foley, Juliana Peloche

Research outputs 2022 to 2026

While design expertise has been widely studied across domains such as industrial design, engineering and architecture, visual communication design has received limited attention. Earlier research examined novice designers’ development of reflective capability, and its link to expertise progression. This study extends that work by investigating how expertise manifests and is fostered among experienced designers within visual communication design practice. Through in-depth interviews with five experienced designers (20–35 years’ industry experience), this qualitative case study employed thematic analysis grounded in Schön’s reflective-practice theory and Lawson and Dorst’s (2013) design-expertise model. This approach enabled close examination of how reflective processes, mentoring structures …

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A Knowledge-Driven, Ai-Assisted Cyber Defence Framework For Iomt Remote Patient Monitoring, Kulsoom S. Bughio, David M. Cook, Abdul M. Unar Jan 2026

A Knowledge-Driven, Ai-Assisted Cyber Defence Framework For Iomt Remote Patient Monitoring, Kulsoom S. Bughio, David M. Cook, Abdul M. Unar

Research outputs 2022 to 2026

The rapid adoption of Internet Medical Things (IoMT) technologies in remote patient monitoring has reshaped healthcare delivery by enabling continuous, real-time clinical observation outside traditional care settings. However, this shift has also expanded the cyber-attack surface across heterogeneous, resource-constrained medical devices, wireless networks, cloud services, and third-party platforms. In cyber warfare, healthcare has become an incorporated target of geopolitics, with hospitals, remote monitoring systems, and emergency health systems being used to broaden the attack surface for adversaries to exploit. Existing security approaches for IoMT environments remain largely manual, fragmented, and reactive, limiting their effectiveness in dynamically assessing vulnerabilities and supporting …

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Renewable And Affordable Energy For Apartments. Inquiry Into Renewable And Affordable Energy For Apartments, Nishadi Ruwandima Weerasinghe Mudiyanselage, Asma Aziz Jan 2026

Renewable And Affordable Energy For Apartments. Inquiry Into Renewable And Affordable Energy For Apartments, Nishadi Ruwandima Weerasinghe Mudiyanselage, Asma Aziz

Research outputs 2022 to 2026

Recent literature identifies a persistent disparity between detached housing and apartments in accessing renewable and affordable electricity. While rooftop solar PV deployment in Australia  has expanded rapidly since 2017, access to these technologies in multi-unit dwellings (MUDs) remains limited, resulting in higher electricity costs for apartment residents compared with standalone houses. This inequity is increasingly significant given rising electricity prices and the growing share of Australians living in apartments.

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Deep Reinforcement Learning–Driven Multi-Omics Integration For Constructing Gtage: A Novel Aging Clock From Igg N-Glycome And Blood Transcriptome, Yao Xia, Syed Mohammed Shamsul Islam, Xingang Li, Abdul Baten, Xuerui Tan, Wei Wang Jan 2026

Deep Reinforcement Learning–Driven Multi-Omics Integration For Constructing Gtage: A Novel Aging Clock From Igg N-Glycome And Blood Transcriptome, Yao Xia, Syed Mohammed Shamsul Islam, Xingang Li, Abdul Baten, Xuerui Tan, Wei Wang

Research outputs 2022 to 2026

Previous studies have demonstrated that the immunoglobulin G (IgG) N-glycome and transcriptome are potential biochemical signatures of chronological and biological ages, and several aging clocks have been developed. By integrating the IgG N-glycome and transcriptome, we propose a novel aging clock, gtAge. We developed a deep reinforcement learning-based multiomics integration method called AlphaSnake. The results showed that AlphaSnake achieved a predicted coefficient of determination (R2) value of 0.853, outperforming the concatenation-based integration method (R2 = 0.820). The gtAge estimated by AlphaSnake explained up to 85.3% of the variance in chronological age, which was higher than that in …

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