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Exploring the Heritage Language Learning and Literacy Practices of Irish-Chinese Children under the Age of Eight within the Family Context: Perspectives and Experiences of Parents and Children
No full textThis study explores heritage language (HL) learning and literacy practices in Irish-Chinese families, focusing on children under 8 years. Grounded in Vygotsky’s (1978) sociocultural theory and supported by Bronfenbrenner’s ecological systems theory, the research examines the
interactions between parents and children in HL learning and explores how language and literacy practices contribute to HL development.
Although the Chinese language is gaining prominence in Ireland and is now included in the Leaving Certificate examinations (CSO, 2023), its role as a heritage language remains underresearched. This study addresses this gap by offering theoretical and practical insights into HL
learning in multilingual contexts. A multi-method approach was employed, encompassing three phases. Phase 1 involved an online
questionnaire completed by 124 Irish-Chinese parents of children aged 0-8, focusing on home language environments and HL literacy practices. In Phase 2, interviews were conducted with 25 children aged 3–8 to capture their perspectives on HL learning and reading. Phase 3 included semistructured interviews with 25 parents to explore their experiences and views. Quantitative data were mainly analysed using descriptive statistics, and qualitative data underwent thematic analysis,
ensuring a comprehensive understanding of HL learning experiences.
Findings show that Irish-Chinese parents actively support HL maintenance through frequent language exposure, early shared reading, and engagement with extended family and community networks, despite limited resources and English dominance. Reading emerged as a significant activity that encourages children’s engagement with their HL, sustains cultural continuity, and strengthens family bonds. The study highlights the need for policy support extending beyond the home to promote early HL learning and literacy, thus reflecting and supporting Ireland’s growing linguistic diversity. Moreover, the study highlights children’s active agency in shaping their language and literacy experiences, driven by sociocultural contexts, familial connections, cultural identity, and personal preferences. These findings emphasise the importance of responsive and child-centred approaches that recognise children as active contributors to HL learning and literacy practices
Affordance as an Interactive Feature to Enhance Usability in Virtual Reality
Get PDFAlthough the use of Virtual Reality (VR) has been steadily increasing in diverse domains thanks to its unique characteristic of immersiveness, the platform is still struggling to enter the mainstream or ubiquitous arena. One of the culprits is the usability: many currently available VR applications exhibit a poor incorporation of design knowledge available in the field of Human-Computer Interaction (HCI). We posit that there are ways to improve the usability of VR applications by more explicitly taking design principles/guidelines into the design of actual interactivity. In this paper, we start exploring this direction by taking one of the most well-known design/usability principles, Affordance, as an explicit end-user feature in navigating a VR environment – this is by visually highlighting only those objects in the surrounding that can be approached and interacted with, so that the users will be aware of what objects they should focus on. We developed a full-fledged VR prototype where a typical household environment with a number of interactable and non-interactable objects are available; recognizing that any forms of highlighting will reduce the sense of immersiveness, the affordance on the interactable objects is only temporarily activated, either automatically in regular time intervals, or a controller button to switch on or off, or a user-maintained interaction in which the affordance is shown only while the user is holding down a controller button. A usability testing with 15 participants revealed a number of insights on how such an explicit incorporation of a design principle could improve the VR interaction
Gendered Citizenship in India Participation and Protest as Acts of Care in the anti-Citizenship Amendment Act/National Register of Citizens movement
Get PDFWhat is our understanding of a ‘women’s movement’? Is it a movement for women by everyone/ a movement by everyone for women/ a movement for women by women/ or all of the above? The existing hetero-patriarchal, nation-state model creates a sociopolitical imaginary where “women’s issues” are feminised; and “national issues” that are matters of greater inclusivity, diversity, and generality are masculinised. This reinstates the framing of citizenship, religious freedom and resource politics as affairs of greater concern, hence masculine; while sexual/domestic violence and reproductive rights are considered specific, and therefore feminine. My research uses the women-led anti Citizenship Amendment Act/National Register of Citizens (anti-CAA/NRC) movement in India to challenge this imaginary. It is structured around a triangular theoretical framework comprising Citizenship, Political Participation, and Social Movements, held together by a Politics of Care. Using in-depth interviews with protestors from the Northeast Indian city of Guwahati and the national capital city of Delhi, it posits that the liberal definition of citizenship fails to capture the lived reality in postcolonial democracies. Instead of treating care as a discrete theme, I approach it as the connective tissue – an epistemic and affective force that links how citizenship is lived, how participation is enacted, and how resistance is sustained. Across both field sites – Delhi and Guwahati – this model allows for a comparative reading of feminist dissent that foregrounds the everyday labour and solidarities that constitute political life from the margins. This thesis, therefore, utilises a historically discrete moment in contentious politics to contribute to the discourse on gendered citizenship in South Asia
Blockchain-Enabled and Latency-Aware Resource Management for Vehicular Networks
No full textVehicular networks have gained considerable attention in recent years, driven by the growing demand for improved road traffic efficiency, autonomous driving capabilities, and onboard entertainment services. Vehicle-to-everything (V2X) communications have emerged as an important aspect of vehicular communications, allowing seamless communication between vehicles and V2X-enabled entities nearby. However, the high mobility of vehicles, scalability issues, different QoS requirements of V2X links, such as varying levels of reliability and stringent latency requirements of certain vehicular applications, and increasing security and privacy concerns of exchanging sensitive data present major obstacles to reliable communications. This work addresses these challenges by proposing novel solutions that enhance vehicular networks’ efficiency, performance, and security. First, a graph-based optimization method is introduced to allocate network resources and fulfill diverse QoS requirements in vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) links. Secondly, to address latency concerns, the Latency-Aware Mode Coordination (LAMOC) algorithm is proposed to minimize end-to-end delays, thereby substantially improving communication reliability in dynamic vehicular scenarios. Additionally, the Blockchain-Enabled Vehicular Edge Computing (BEVEC) framework is proposed to build upon the need for secure and efficient service delivery. BEVEC integrates a dual-layer verification process using a permissioned blockchain to ensure data integrity and a Deep Reinforcement Learning (DRL) algorithm that optimizes a tailored utility function. This synergy achieves timely and energy-efficient service delivery while improving reliability. Moreover, to address the multifaceted challenges of dynamic vehicular networks—ranging from energy efficiency to privacy and scalability—a multi-layer Permissioned Distributed Ledgers (PDL)-based Cooperative Decentralized Vehicular Edge Computing (PDL-CoDeVEC) framework is introduced. A Multi-Agent Deep Reinforcement Learning (MADRL) algorithm, named Multi-Agent Cooperative Task Coordination (MACTAC), is proposed to optimize the trade-off between local and offloaded task processing that enables vehicles to independently make computation decisions while preserving real-time performance through utility maximization. Finally, a dynamic rolling-horizon resource allocation algorithm combined with a Vickrey–Clarke–Groves (VCG) pricing mechanism is proposed to address the dual challenges of efficient resource allocation and fair incentive schemes in IoV networks. Extensive simulations were conducted across diverse scenarios to evaluate the proposed solutions. The results demonstrate notable latency and energy consumption reductions, as well as improved throughput and task completion rates. These findings validate the efficacy of the proposed mechanisms in real-time vehicular environments, supporting their potential for large-scale deployment while maintaining robust security and privacy safeguards
Multimodal Deep Learning for Driver Monitoring: Integrating EEG and Vision for Robust Drowsiness Detection and Safety Enhancement
Get PDFRoad accidents remain a major global concern, with driver drowsiness and delayed reaction times recognized as key contributing factors. This thesis advances driver-monitoring research by developing multimodal approaches that integrate electroencephalography (EEG) and vision data to predict reaction times and drowsiness. The investigation first demonstrates that pre-stimulus EEG signals—specifically spectral power in the alpha and theta bands—contain rich information for estimating reaction times to critical road events. Using subject-independent machine-learning pipelines, short EEG windows recorded before event onset effectively differentiate between fast and slow responses. The work then explores the benefits of incorporating vision data as a second
modality by fusing EEG signals with camera-based observations of the driver. One branch converts EEG power-spectral-density features into image-like representations for analysis with deep convolutional neural networks and transformer models. Another branch directly integrates raw EEG signals with synchronised video frames through end-toend multimodal transformer architectures. Results indicate that transformers equipped with cross-modal attention capture complex interdependencies between neural and visual cues, yielding significant improvements in driver-drowsiness detection over unimodal approaches. Real-time deployment is addressed by designing and optimising a lightweight pipeline for edge-based processing. This resource-efficient model enables rapid analysis of facial cues under diverse driving conditions, ensuring operation on embedded platforms such as smartphones and automotive edge devices. Extensive evaluations on large-scale simulated datasets confirm the generalisability of the proposed approaches across varied driving scenarios. Experiments reveal that transformer-based fusion significantly enhances predictive performance by effectively combining complementary neural and visual cues. Moreover, the lightweight pipeline maintains high accuracy under stringent computational constraints, enabling real-time, ondevice deployment
Integrated Life Cycle Assessment of Residential Retrofit Strategies: Balancing Operational and Embodied Carbon, Lessons from an Irish Housing Case Study
Get PDFThe residential building sector is a major contributor to global energy consumption and carbon emissions, making retrofit strategies essential for meeting climate targets. While many studies focus on reducing operational energy, few comprehensively evaluate the trade-offs between operational savings and the embodied carbon introduced by retrofit
measures. This study addresses this gap by developing an integrated, novel scenario-based assessment framework that combines dynamic energy simulation and life cycle assessment (LCA) to quantify whole life carbon impacts. Applied to representative Irish housing typologies, the framework evaluates thirty retrofit scenarios across three intervention
levels: original fabric, shallow retrofit, and deep retrofit incorporating multiple HVAC technologies and envelope upgrades. Results reveal that while deep retrofits deliver up to 80.2% operational carbon reductions, they also carry the highest embodied emissions. In contrast, shallow retrofits with high-efficiency air-source heat pumps offer near-comparable
energy savings with significantly lower embodied impacts. Comparative analysis confirms that reducing heating setpoints has a greater effect on energy demand than increasing system efficiency, especially in low-performance buildings. Over a 25-year lifespan, shallow retrofits outperform deep retrofits in overall carbon efficiency, achieving up to 76% total emissions reduction versus 74% for deep scenarios. Also, as buildings approach near-zero energy standards, the embodied carbon share increases, highlighting the importance of LCA in design decision-making. This study provides a scalable, evidence-based methodology
for evaluating retrofit options and offers practical guidance to engineers, researchers, and policymakers aiming to maximize carbon savings across residential building stocks
A Novel Methodological Assessment of Reverse Osmosis Desalination under Variable Operating Conditions using Performance – Power – Economic Analysis: A Multi-disciplinary Approach
No full textReverse Osmosis (RO) has become one of the world’s leading technologies for desalination purposes. The technical maturation of membrane materials and hydraulic devices has further enabled its deployment across many applications ranging from municipal freshwater production to industrial wastewater reuse. This
widespread and increasing deployment of RO, often with sector-specific objectives and tailored configurations, coupled with the growing use of renewable energy sources, has made it quite common for RO treatment plants to operate outside their intended design. Accommodating the scale and spatial salinity range at which these processes must operate has resulted in current modelling approaches no longer being suitable in fully characterising plant process variables over an extended range of operation. These modelling inaccuracies, originating from the assumption of certain fixed parameters, has compounding effects on other subsequent areas of the RO system, ultimately leading to misinformed predictions of membrane performance, energy efficiency and plant running costs. Importantly, the aforementioned limitations hinder the
development of new treatment strategies over a wider range of operation. A pilot scale RO process was designed and developed. Subsequently, a detailed experimental study was undertaken to validate relevant physicochemical, electromechanical and economic models, to better understand the interplay of certain technical and economic process variables. The final outputs from all three models combine to form the Performance–Power–Economic (PPE) methodological approach to help improve upon the efficacy, efficiency and feasibility of RO plant configurations over a wide range of operating conditions. The proposed method can be indirectly applied to new or pre-existing RO systems to greater
define: (a) membrane separation performance; (b) electrical and hydraulic component efficiencies and (c) the feasibility and cost-effectiveness of overall treatment
Mitigating Interruptions in Digital Reading: Strategic Pauses and Note-Taking for Enhanced Cognitive Performance
Get PDFThis study investigates how structured interventions—specifically pausing at natural breakpoints and guided note-taking—affect cognitive performance, memory retention, and task continuity in digital reading. We introduce SmartPause, a context-aware bookmarking system that nudges users to pause at meaningful points and externalise insights through lightweight notes. In a controlled experiment (N = 51), participants were assigned to one of three conditions: (1) interruption at an arbitrary point, (2) guided pause at a natural breakpoint, or (3) guided pause with note-taking. Results reveal that guided pauses, particularly when combined with note-taking, significantly enhance long-term memory retention while having no measurable impact on perceived cognitive load or selective attention. These findings highlight the potential of digital tools to support cognitive load management and task continuity by structuring interruptions in alignment with natural cognitive rhythms. The high usability rating of SmartPause underscores its practical applicability across e-reading platforms. This study contributes to human-computer interaction (HCI) by integrating principles from cognitive science into design solutions that enhance comprehension and information retention. Future research should explore personalised interventions, extended retention intervals, and real-world deployment to further optimise cognitive load in digital reading contexts
Skin-derived volatile organic compounds trigger redox signalling pathways in human keratinocytes via gas-phase interaction
Get PDFHuman skin emits a diverse range of volatile organic compounds (VOCs) originating from both endogenous metabolic activity and microbial transformation of sweat and sebum. While these volatiles have been
profiled extensively, their potential to influence host cellular processes remains largely unexplored. In this study, we investigate the capacity of five skin-relevant VOCs—nonanal, decanal, 6-methyl-5-hepten2-one (6MHO), acetic acid (AA), and 2-ethyl-1-hexanol (2EH) – to induce redox signalling pathways in keratinocytes. We demonstrate that selected compounds, particularly nonanal, decanal and AA, induce
intracellular reactive oxygen species (ROS) and activate the Nrf2–Keap1 antioxidant defence mechanism. Using both conventional liquid-phase treatment and a custom-designed headspace system for gasphase treatment, we show that these VOCs elicit this signalling response from both liquid and gas phases. These findings provide the first mechanistic evidence that endogenous or microbially-derived VOCs from skin can function as gaseous redox modulators, capable of triggering protective cellular responses from a distance. This work presents new evidence for cell–cell volatile communication in skin and through its resident microbiota, offering insights into the signalling potential of volatile metabolites
Psychological Readiness is the Main Barrier to Return to Play After Revision Anterior Cruciate Ligament Reconstruction
Get PDFDespite advances in modern surgical techniques, return-to-play (RTP) rates after revision anterior cruciate ligament reconstruction (R-ACLR) often fall short of patients’ expectations. There is growing awareness that a patient’s psychological recovery is as important as the functional recovery of their knee