Developing predictive models for computing the mechanical behaviour of soil structure interaction problems involving sandy materials

Integrate a FEA software with a new soil material model and use it to generate a dataset of Soil Structure Interaction results to train Artificial Intelligence algorithms.Curren

Development of predictive models for the assessment of the wind turbine foundation's lifespan and structural integrity using ML algorithms

Wind turbine foundations are critical components of renewable energy infrastructure, designed to support substantial dynamic loads and withstand environmental conditions throughout their operational life. While wind turbine superstructures typically have an operational life of 20 years, the reusability of the foundation beyond this period remains largely unexplored. This research addresses the ageing and degradation of wind turbine foundations, focusing on developing predictive models to assess their long-term structural integrity and potential for reuse. Utilizing advanced numerical modelling techniques, structural health monitoring (SHM) and material property validation, this study will generate a dataset to determine the ultimate limit state (ULS) capacity of wind turbine foundations at various stages of ageing. This dataset will be used to train machine learning algorithms, resulting in developing predictive models that can inform decision-making on the reusability of ageing foundations for new wind turbines. The project also aims to validate models for concrete ageing and degradation with real-world data from in-situ structures, enabling realistic assessments of foundation performance over time. Additionally, the research will explore innovative foundation designs, retrofitting strategies, and strengthening techniques to extend foundation life, thereby contributing to a more sustainable energy infrastructure. The outcomes will provide valuable insights into foundation reusability, SHM integration, lifespan optimization, and cost-effective design strategies for the renewable energy sector.Curren

Systematic literature review of the factors of information sharing that enable circular procurement in the construction industry

Construction is a fundamental sector in most economies, and its high consumption of physical resources presents major opportunities for applying circular economy principles to minimise waste and improve sustainability. Procurement functions at the intersection of construction supply chains, managing design, purchasing, and material sourcing activities. Effective information sharing both within and between organisations is essential for embedding circular economy principles into procurement processes. This paper adopts a systematic literature review approach to identify and synthesise research on information sharing in circular procurement. Descriptive analysis outlines the research trends, theoretical and methodological orientations, and geographical distribution of studies, while synthesis categorises barriers and enablers of information sharing across micro, meso, and macro-organisational levels. Additionally, circular economy-related information and knowledge management activities, such as creation, dissemination, and application, are mapped against stages of the strategic procurement process and the Royal Institute of British Architects Plan of Work, strengthening the study’s relevance to construction practice. By integrating fragmented yet expanding bodies of literature, the paper provides a comprehensive understanding of how circular economy information and knowledge management intersect with procurement in construction. It offers a construction-specific framework that embeds circularity throughout the procurement lifecycle, with support from the Resource-Based View and Institutional theory and also identifies key organisational enablers and barriers. The review also highlights limited empirical and theoretical integration in current research and recommends future studies that apply behavioural and organisational theories to explore knowledge-sharing dynamics, examine policy impacts, and assess the role of technology and skills development in advancing circular procurement

Assessing ChatGPT’s legal reasoning in statutory land consolidation: The case of Cyprus

Land consolidation remains a cornerstone of rural development, but its implementation is often hindered by complex statutory frameworks and lengthy procedures. In Cyprus, where land consolidation has historically reduced fragmentation, the process faces new challenges amid declining agricultural importance and evolving policy priorities such as climate change resilience, sustainable development, and urban land readjustment. At the same time, artificial intelligence (AI) and large language models (LLMs) like ChatGPT are increasingly being considered as tools to support legal and planning processes. This study provides the first systematic evaluation of ChatGPT’s capacity to interpret and respond to legal questions derived from Cyprus’s Land Consolidation Law. Using a corpus of 100 questions across four levels of legal complexity, responses were assessed with a rubric measuring correctness, completeness, clarity, and interpretive depth. The results show strong performance in basic factual and procedural questions (98% accuracy for Type 1), moderate reliability in procedural and hypothetical reasoning (84% and 82% respectively), but significant decline in complex interpretive tasks (55% for Type 4). These findings highlight both the potential and the limitations of LLMs in statutory interpretation: they can provide accessible explanations and procedural guidance but cannot yet replace expert legal reasoning in ambiguous or high-stakes cases. The study contributes to the emerging discourse on AI in land policy and rural development, offering methodological insights for evaluating LLMs in domain-specific legal contexts and outlining implications for their responsible integration into planning, cadastral, and governance workflows.No funding used

Reforming schools into health promoting schools: perspective based on expert consensus from a European multistakeholder consultation

Every school on this planet should aim to become a healthy school. This is the motto of the WHO/UNICEF health promoting school strategic agenda (HPS). To address gaps and needs of children's health and educational inequalities in schools, a qualitative study was set up to synthesize experts' views and insights on school health programs and the HPS strategy in Europe. This multi-stakeholder consultation took place during an international children's health workshop in Cyprus (October 2024). Data was collected through focus group interviews with ~ 30 experts engaged in a multistakeholder consultation between academics, governmental officials, teacher liaisons, and health professionals, including WHO experts and NGOs. The consultation identified the following themes: systemic limitations in funding and sustainability of health education/promotion programs, enhanced curriculum needs for health literacy, limitations in school physical environment, rise in behavioral risk factors among children and adolescents, and growing mental health needs. A consensus was reached regarding the prerequisites and recommendations towards improving both health and educational outcomes for children; the implementation of holistic methodological frameworks, such as that of the human exposome and its exposomics tools were collectively proposed to better deploy the HPS recommendations in the school community.Open access funding provided by the Cyprus Libraries Consortium (CLC)

Augmented reality for story-related activities in primary and secondary education: a systematic review

Story-related activities such as storytelling, story creation and narrative-based learning have become a popular pedagogical approach used in education. Additionally, Augmented Reality (AR) is a tool that receives significant attention globally. Recognizing this trend, researchers have been seeking ways to integrate story-related activities with AR in educational contexts. This paper presents a systematic literature review focusing on the use of AR in story-related activities within primary and secondary education. By conducting a systematic search of studies published in the past 5 years between 2019 and 2024, 264 relevant papers were initially identified. After applying inclusion, exclusion and quality criteria, 39 studies were selected for in-depth analysis. Framed by the principles of learning experience design, this review explores how AR is integrated into story-based educational practices, highlighting its current applications, benefits, and barriers. Additionally, the review critically reflects on the need to prioritise pedagogy over technological features when designing AR-enhanced learning experiences. The study concludes with recommendations for future research and practical insights for educators aiming to incorporate AR into story-related educational activities.Open access funding provided by the Cyprus Libraries Consortium (CLC). This work has been funded by the Erasmus + Programme of the European Union, funding number: 2023-1-MT01-KA220-SCH-000154134 (Project: CARS: Children as Creators of Augmented Reality Stories)

Combining User and Venue Personality Proxies with Customers’ Preferences and Opinions to Enhance Restaurant Recommendation Performance

Recommendation systems are popular information systems that help consumers manage information overload. Whilst personality has been recognised as an important factor influencing consumers’ choice, it has not yet been fully exploited in recommendation systems. This study proposes a restaurant recommendation approach that integrates customer personality traits, opinions and preferences, extracted either directly from online review platforms or derived from electronic word of mouth (eWOM) text using information extraction techniques. The proposed method leverages the concept of venue personality grounded in personality–brand congruence theory, which posits that customers are more satisfied with brands whose personalities align with their own. A novel model is introduced that combines fine-tuned BERT embeddings with linguistic features to infer users’ personality traits from the text of their reviews. Customers’ preferences are identified using a custom named-entity recogniser, while their opinions are extracted through structural topic modelling. The overall framework integrates neural collaborative filtering (NCF) features with both directly observed and derived information from eWOM to train an extreme gradient boosting (XGBoost) regression model. The proposed approach is compared to baseline collaborative filtering methods and state-of-the-art neural network techniques commonly used in industry. Results across multiple performance metrics demonstrate that incorporating personality, preferences and opinions significantly improves recommendation performance

When Nudges Backfire: A Distinction Between Spillovers and Misfires

The concept of nudging (libertarian paternalism) has been eagerly adopted in the design of digital behavioural interventions, yet discussion on adverse effects of nudges has been limited. In an attempt to enhance resolution, this theoretical paper conceptually differentiates two types of adverse effects, namely, spillovers and misfires. We propose that contrary to behavioural spillovers that occur as a consequence of a targeted behaviour, the causality of misfires is primarily attributed to the nudge type. In doing so, we employ visual representations of the behavioural trajectories that demonstrate intended and unintended effects of nudges to support choice architects in blueprinting intervention processes. We differentiate between spillovers and misfires by summarizing key empirical research that seeks to explain the causes of each and the contextual nature that distinguishes them. We conclude by drawing implications for the design of technology-mediated nudges as well as the role of its timing

A Demo of Google Inject

We present a demo of Google Inject, a technology-mediated nudge aimed at increasing users’ engagement with fact-checks by injecting fact-checking articles, relevant to one’s query, at the top of Google search results. We elaborate on the problem that Google Inject aims to address, the design and development of the tool, and our ongoing and future empirical work to test its effectiveness in changing individuals’ behaviors