6277 research outputs found
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TwinGuard: privacy-preserving digital twins for adaptive email threat detection
No full textEmail continues to serve as a primary vector for cyber-attacks, with phishing, spoofing, and polymorphic malware evolving rapidly to evade traditional defences. Conventional email security systems, often reliant on static, signature-based detection struggle to identify zero-day exploits and protect user privacy in increasingly data-driven environments. This paper introduces TwinGuard, a privacy-preserving framework that leverages digital twin technology to enable adaptive, personalised email threat detection. TwinGuard constructs dynamic behavioural models tailored to individual email ecosystems, facilitating proactive threat simulation and anomaly detection without accessing raw message content. The system integrates a BERT–LSTM hybrid for semantic and temporal profiling, alongside federated learning, secure multi-party computation (SMPC), and differential privacy to enable collaborative intelligence while preserving confidentiality. Empirical evaluations were conducted using both synthetic AI-generated email datasets and real-world datasets sourced from Hugging Face and Kaggle. TwinGuard achieved 98% accuracy, 97% precision, and a false positive rate of 3%, outperforming conventional detection methods. The framework offers a scalable, regulation-compliant solution that balances security efficacy with strong privacy protection in modern email ecosystems
Rethinking critical race theory: education against elimination in a time of genocide
No full textThis open access book outlines a framework to explain how a world system of white supremacy is reproduced through education at national and local levels. This contribution thus addresses the important need for critical race education scholarship that is not limited by nationally-framed or American-centric perspectives. Written in an accessible manner, the framework recognises that racism takes hold in diverse ways in local and national educational contexts, but is ultimately rooted in global white supremacy. Forging links between Critical Race Theory and decolonial thought, this framework explains how national racialized social systems are reproduced through global structures, knowledge, and feelings; and articulates how anti-racism in education relies on forging transnational solidarities. To illustrate the relevance and significance of this framework, the book engages with how educational systems throughout the world are implicated in sustaining global anti-Muslim racism in a time of Palestinian genocide. Addressing a timely topic and gap in the literature, this book will provide an invaluable resource to postgraduate students and academics developing critical scholarship that explains and resists the global nature of race and racism in education
The Counterfactual–Dialectical Optimization Framework: a prescriptive approach to employee attrition management with empirical validation
No full textEmployee attrition represents a significant burden, yet predictive models often fail to provide actionable retention strategies, creating a critical prediction–prescription gap. This paper introduces the Counterfactual–Dialectical Optimisation (CDO) framework, a novel methodology that bridges this gap by integrating predictive modeling, robust causal inference, and budget-constrained optimization. We first illustrate the framework’s mechanics on the synthetic Human Resources (HR) dataset, then conduct a rigorous proof-of-concept on the empirical ‘Saudi Employee Attrition Dataset’ to test its real-world applicability. In our empirical validation, we employ Propensity Score Matching (PSM) to estimate the causal effects of interventions while controlling for confounding variables. The results on the real-world dataset show that while predicting attrition is challenging Area Under the Curve (AUC ≈ 0.60), the framework successfully identified a deserved promotion as a powerful retention lever, causally reducing attrition probability by an estimated 23.9 percentage points. Acting on this insight, the optimization layer efficiently allocated the entire budget to this single, high-impact strategy for high-priority employees. This work provides a validated blueprint for shifting from passive prediction to active, Return on Investment (ROI)-driven prescription in strategic workforce management, demonstrating how to derive clear, actionable guidance even from complex, real-world data
Building trustful relationships through intrapreneurship in Academic Development
No full textTrust between people who develop academics (Academic Developers) and academics is not always straightforward, and where trust does exist, it can often be limited to the individuals involved in the interaction, rather than extending to the wider institutional culture. This lack of trust can be attributed to a variety of factors, one of which is the perception that Academic Developers are merely a management tool focused on performance metrics rather than upholding quality standards. Academic Developers' cognitive authority can also be challenged by institutional and administrative authority, affecting trust between academics and developers. This reflection aims to explore barriers to the development of trust between Academic Developers and academics before proposing changes in practice to bridge the trust gap. The main focus of this reflection is to scale trust beyond individual relationships and promote a culture of trust within the institution. By doing so, we advocate for an approach that works towards building a more trusting environment in HE that fosters collaboration, creativity, and success, given that Academic Developers' role as a ‘broker’ between the institution and colleagues is becoming more prevalent. We argue, however, that efforts to achieve more robustly trustful relationships between Academic Developers and the communities they serve require investment, buy-in and championing by senior executive teams to ensure Academic Developers are themselves appropriately developed to fulfil their potential. As such, we propose a framework for building trust through integrating intrapreneurship in Academic Developer CPD activity
Danse mes playfellows – exploring French through musical theatre
No full textOutside. A group of Playful Learning delegates gather. The task is to devise a short piece of movement to the song Les sans papiers from the musical Notre Dame de Paris. Three groups engage with their local environment to influence their storytelling. Their reflections, together with interjections from the session facilitator, offer an insight into their process of using musical theatre to explore the French language
Responses to monetary policy uncertainty: an asymmetric analysis of money supply and demand
No full textThis study aims to examine the symmetric and asymmetric effects of uncertainties in US monetary policy on money demand between 2000: M1 and 2025: M5.To this end, this study explores and uses the recently developed monetary policy uncertainty (MPU) index, applying both linear and nonlinear autoregressive distributed lag (ARDL) models to the USA. The linear model could not find a significant effect of MPU on money demand (M2).The linear model could not find a significant effect of MPU on M2. However, empirical findings of the nonlinear ARDL indicate that uncertainties in monetary policy have essential impacts on M2. While rises in the MPU index decrease the demand for money, falls in the index increase in the long run. This can be interpreted as meaning that rising uncertainty in the MPU increases uncertainty about future interest rates, inflation and economic growth expectations, and individuals may become more cautious about spending or investing. However, when uncertainty decreases, Americans tend to increase their demand for money.Using the MPU index − rather than broader uncertainty indicators such as the EPU − provides a more focused perspective on monetary dynamics. Crucially, the findings offer forward-looking insights into how Americans may adjust their money-holding behavior in response to potential increases in MPU driven by evolving Federal Reserve policies under the current US administration’s 2025 high-tariff economic agenda. This enhances the study’s policy relevance for anticipating behavioral responses to future uncertainty
Sensitivity analysis of WRF-CMAQ model in predicting PM2.5 and O3 concentration in Peninsular Malaysia: 2019 transboundary burning smoke case study
No full textThe high PM2.5 concentrations significantly influence the air quality in the Maritime Continent region, especially in Peninsular Malaysia (PMY), which is affected by the annual burning season. However, the 2019 pollution case is unique due to the presence of a positive Indian Ocean dipole (pIOD) with a weak El Niño, which influenced the transport of pollutants toward PMY. This work aims to evaluate the ability of the numerical chemical weather prediction model (WRF-CMAQ) by performing a sensitivity analysis to reproduce the air quality during this event. Two model settings were studied: weather nudging and the burning emission amount of the fire inventory from NCAR (FINN). Three cases were established: 1) WRF-CMAQw (without nudging setting and with original fire emission), 2) WRF-CMAQn (with nudging setting and with original fire emission), and 3) WRF-CMAQa (with nudging setting and adjusted fire emission) to predict the PM2.5 concentration in PMY during the 2019 transboundary smoke event. The weather (temperature and wind profile) simulation results showed that WRF-CMAQa and WRF-CMAQn agreed up about 95 % and WRF-CMAQw agreed up to 93 % when compared with ground weather stations based on the statistical evaluation of correlation coefficient, bias, and error measures. For air quality, overall, WRF-CMAQa (87.23 %) demonstrated better performance compared to WRF-CMAQw (62.41 %) and WRF-CMAQn (78.72 %) in predicting the ground PM2.5. However, the diurnal prediction during the transboundary smoke event remains weak. For O3 concentration, the model performance agreement was quite low for all simulations. However, WRF-CMAQa could predict about 44.76 % compared to WRF-CMAQn (26.66 %) and WRF-CMAQw (41.90 %) in overall model performance, and all simulations managed to capture the diurnal trend of O3 when compared with ground observation station data. In conclusion, the sensitivity study on the weather and chemical prediction model, especially WRF-CMAQ, could help improve the air quality prediction system in PMY during the recurrence of transboundary smoke events
Creation of a novel coding program to identify genes controlled by miRNAs during human rhinovirus infection
No full textHuman rhinovirus (RV) is the most frequent cause of the common cold, as well as severe exacerbations of chronic obstructive pulmonary disease (COPD) and asthma. Currently, there are no effective and accurate diagnostic tools or antiviral therapies. MicroRNAs (miRNAs) are small, non-coding sections of RNA involved in the regulation of gene expression and have been shown to be associated with different pathologies. However, the precise role of miRNAs in RV infection is not yet well established. Also, no unified computational framework exists to specifically link miRNA expression with functional gene targets during RV infection. This study aimed to first analyse the impact of RV16 on miRNA expression across the viral life cycle to identify a small panel with altered expression. We then developed a novel bioinformatics pipeline that integrated time-resolved miRNA profiling with multi-database gene-phenotype mapping to identify diagnostic biomarkers and their regulatory networks. Our in-house Python-based tool, combining mirDIP, miRDB and VarElect APIs, predicted seven genes (EZH2, RARG, PTPN13, OLFML3, STAG2, SMARCA2 and CD40LG) implicated in antiviral responses and specifically targeted by RV16 and regulated by our miRNAs. This method therefore offers a scalable approach to interrogate miRNA-gene interactions for viral infections, with potential applications in rapid diagnostics and therapeutic target discovery
Multiple knowledge depiction of digital twin-driven circular economy: concepts, integrated advanced technologies, triple bottom line of smart construction, and exploratory case studies
No full textOngoing global issues arising from rapid societal and economic development intensify resource extraction, ending in waste and emissions. Digital technology-empowered circular economy (CE) practices potentially encounter these issues, leading to sustainable development (SD). Digital twin (DT), a building block of emerging digital technologies, is extensively employed to automate and modernize construction phases and services. However, the broader research body reflects knowledge gaps and evidence inadequacies. This study seeks to disseminate awareness of DT and how its adoption reinforces confidence in CE practices, prospectively nurturing the way for triple bottom line (TBL) sustainability in construction. The study comprehensively and rigorously reviews DT deployment with a customized focus on building construction, delving into and analyzing the significance and bottlenecks. This research endeavors to apprise evidence of DT-driven CE uptake in the Kingdom of Saudi Arabia (KSA), which has launched Vision 2030 to steer its nation towards a vibrant society, ambitious nation, and thriving economy. A four-step methodology is adopted for exploratory research case studies with a literature review. Pertinent literature is collected, focusing on 2020–2024. Subsequently, multiple cases from the KSA are explored to corroborate the phenomenon under scrutiny. Key findings discovered that DT capabilities enhanced with other technologies and tools strengthen physical and cyber systems and data infrastructure. DT-navigated CE shares a plethora of social, economic, and environmental opportunities in residential, industrial, and commercial buildings. This study encompasses theoretical and practical implications. It offers comprehensive insights into visionary concepts for the research community and construction industrialists, nurturing their understanding and motivating them to implement DT for CE catalysis, resulting in a multitude of TBL sustainable advantages. Besides, it bridges the gap between literature and practical real-world practices. The developed interdisciplinary framework enhances DT application feasibility in construction services within the boundaries of architecture, engineering, construction, and procurement services
Framework for a customised approach to simulated practice learning design
No full textThe 'Framework for a Customised Approach to Simulated Practice Learning Design' provides support for users to design simulated practice learning based on stakeholder needs, while ensuring feasibility and sustainability. Using a collaborative approach, the framework and its supporting guide supports users to prepare students for clinical practice through targeted learning that bridges theory and practice, addressing quality through simulation guidelines and Professional, Statutory, Regulatory Standards. It does this through a simple four step approach - step 1: identifying purpose, step 2: defining scope, step 3: writing learning outcomes, and step 4: designing SPL.Demonstrating rigour, the framework was created through the integration of educational theories, critical insights, empirical evidence, and literature on simulated practice learning. With its underpinning pragmatist methodology, it aims to be adapted according to user needs, encouraging flexibility in its adoption. Although it is primarily designed for undergraduate nursing programmes in a University setting, the author encourages scalability to other settings and professional groups
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