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Extracting airline emission KPIs from sustainability reports using large language models (LLMs)
Get PDFThe extraction of environmental Key Performance Indicators (KPIs) from airline sustainability reports is essential for assessing environmental sustainability metrics and regulatory compliance within the European aviation sector. Manual extraction from extensive, unstructured documents is laborious and often inconsistent. This study systematically investigates the potential of advanced Large Language Models (LLMs) –specifically − GPT-4.0, o3- mini, and Deepseek R1- to automate the extraction of emissions-related KPIs from the 2023 sustainability reports
of 16 publicly traded European airline groups. Utilizing the Perplexity platform, the research contrasts manual expert extraction with automated approaches, exploring various models, prompt strategies, and data formats. Results indicate that the accuracy of LLM extraction depends significantly on prompt specificity. Attempts to extract data from unstructured documents without guidance yielded low accuracy. However, incorporating explicit KPI terms into prompts increased accuracy from below 30% to above 70%. The format of the data source
was also influential, with HTML formats producing superior extraction results compared to PDFs. Despite ongoing challenges in standardizing data and extracting precise KPI metrics, the findings demonstrate that LLMs can substantially streamline environmental, social and governance (ESG) data collection when prompt engineering and source standardization are prioritized. This study represents a novel, interdisciplinary approach by combining advances in large language models (LLMs) with expertise in environmental, social, and governance
(ESG) analysis within the aviation sector, offering empirical benchmarking of LLM performance in real-world regulatory contexts. Recommendations for LLM integration into ESG analysis workflows are provided, and
future research directions for advancing automation in sustainability reporting are discussed
Unheard voices: The critical role of nurses and midwives in climate resilience and disaster preparedness in Small Island Developing States
Get PDFIsland nations such as Barbados, Jamaica, and Tonga face rising threats from climate change, including hurricanes, flooding, and sea-level rise. Nurses and midwives are crucial frontline responders, leading
disaster preparedness, emergency care, and community recovery. This paper highlights their leadership, resilience, and innovation in addressing the health impacts of climate-related disasters. Drawing on realworld examples, it shows how these professionals bridge clinical care with public health strategies, ensuring vulnerable populations receive timely, culturally appropriate interventions. Through education, emergency planning, and clinical support, they foster resilience and recovery. The experiences from these islands emphasize the urgent need to strengthen nursing and midwifery leadership within climate adaptation efforts. Recognizing and investing in their role is vital to building sustainable, climate-resilient health systems in Small Island Developing States (SIDS). The paper calls for increased policy support, funding, and
capacity-building to empower nurses and midwives as essential agents of change
Personalization and Elite Rhetoric: How the Autocrat's Popularity and Political Repression Influence Policy Speech of Regime Officials
Get PDFWe study the implications of regime personalization on the incentives of political elites to politicize their policy agenda and express loyalty to the ruler. Because revering the autocrat is one of the observable manifestations of personalization, while the process of personalization may be, in turn, influenced by an increased prevalence of leader-centered rhetoric, isolating the effects of personalization on policy and political rhetoric is difficult. We distinguish between the negative, fear-driven motivation to politicize speech by regime officials and the positive motivation linked to their expectations of regime durability. The former is
influenced by political repression, whereas the latter is moored to the ruler's poll standing—of importance for electoral autocracies in particular. Drawing from over 1000 annual legislative addresses of Russian governors in 2007–2023, we show that elites politicize their rhetoric following arrests of their peers, and they also closely track the autocrat's popularity. We contribute to the literature on personalization and authoritarian speech
Health literacy research on the island of Ireland: a systematic review
Get PDFConsistently, low health literacy has been found to lead to poorer health outcomes, both internationally, and in Ireland. Given this knowledge,
there is a need to understand key thematic trends, methodological approaches and evidence gaps in policy and practice. Seven electronic
databases (Science Direct, MEDLINE, CINAHL Complete, Web of Science, Scopus, PsychoINFO, and SPORTDiscus) were searched between October and December 2023 focusing on studies published in English between 2013 and 2023. Initial peer reviewed records (N = 551) were screened resulting in 37 studies included in this review. Narrative analysis indicated that across the island of Ireland many studies had narrow populations of focus (e.g. Dublin based, adults, chronic illness populations), limited research design and methodologies (e.g. cross-sectional, narrative, and primary research with short time frames), and lacked rigorous monitoring and evaluation of health literacy as a primary or secondary outcome. Future health literacy research in Ireland should consider: (i) contextual and sociodemographic factors (age, sex,
ethnicity, socioeconomic status) when aiming to improve health literacy in different populations, (ii) exploring health literacy beyond the
clinical domain, (iii) advocating for sustainability of effective programmes, and (iv) rigorous, longitudinal evaluation of health literacy. Quality
research in these areas will support the meaningful and sustainable development of health literacy in Ireland, with findings that can be
transferred internationally
Age-related hearing loss and dementia risk across the lifespan: mechanisms, equity, and prevention
Get PDFAge-related hearing loss (ARHL) has emerged as a significant and potentially modifiable risk factor for neurodegenerative disorders, including Alzheimer’s disease. A growing body of evidence links ARHL to structural and functional changes in the brain, with implications for cognitive decline and dementia onset. However, both ARHL
and dementia are multifactorial conditions shaped not only by biological mechanisms but also by broader social determinants of health. Inequities in access to hearing care, underrepresentation of marginalised populations in research, and variability in intervention outcomes emphasise the need for a more inclusive and integrated
approach to prevention. This review synthesises current evidence on the neurocognitive consequences of ARHL, the potential mechanistic pathways linking hearing loss to dementia, and the role of inequity. It includes a novel perspective by highlighting the need for cross-cultural, population neuroscience approaches incorporating exposome and equity frameworks that capture phenotypic variability across diverse populations. This review outlines key priorities for advancing neurocognitive and translational research on hearing loss, neurodegeneration, and global health equity. Addressing these gaps is essential to developing equitable strategies for dementia prevention and optimising cognitive health across the lifespan
Design and Development of an Interactive AI Toolkit for Engaging Older Adults in AI Discussions
Get PDFThis paper presents the design and development of a low-cost, interactive Artificial Intelligence (AI) toolkit in the form of an animatronic ‘talking’ mask. The toolkit aims to democratise AI and make it more accessible, particularly for older adults, by facilitating hands-on engagement with AI technologies and engaging them in meaningful discussions about its opportunities and potential drawbacks. The toolkit is built using customisable features such as replaceable face, jaws and eyes, and modular software features like face tracking, speech recognition, speech-to-text and text-to-speech engines, and large language model (LLM). The customisable design provides a means to explore perceptions, raise awareness and encourage healthy discussions about different facets of AI, especially amongst technologically-challenged populations. It promotes co-design opportunities by leveraging its customisability to allow for adaption of its features to suit the technical abilities and preferences of the audience. Designed with an open-source approach, the project also encourages collaboration among makers and developers, fostering community-driven enhancements and adaptations. This accessibility empowers others to build upon the design, contributing to its evolution as a versatile tool for education and outreach. Evaluation of the platform with 3 distinct user groups highlights its potential to demystify AI technologies and engage diverse audiences in a conversation about the challenges and opportunities they present. This paper concludes with the identification of future opportunities for this research, including the use of co-creation methodologies with end users to extend the work to suit their needs and provide a public engagement framework for understanding emerging technologies
Statistical Data Processing Technologies for Sustainable Aviation: A Case Study of Ukraine
Get PDFAviation is widely recognised as a system of systems where interconnected components interact dynamically within a structured framework. Failures in aviation equipment, inconsistencies in technological procedures, and operational inefficiencies contribute to stochastic variability, making robust data-driven approaches essential for enhancing sustainability and resilience. This study proposes a comprehensive statistical data processing framework aimed at enhancing the sustainability and resilience of civil aviation systems, using Ukraine as a case study. Our analysis identifies two major gaps: an insufficient application of modern data processing techniques and a lack of consideration for the changepoint effect—a critical factor influencing reliability indicators, diagnostic parameters, and technological process trends. The scientific novelty and value of this article lie in the development of a new approach to data processing in civil aviation, which includes a set of methods for changepoint detection, the estimation of the model parameters after the changepoint, and the prediction of future values in trends of processed data. The practical value is associated with the possibility of implementing such processing for all components of civil aviation, where process parameters and trends of diagnostic variables for components of civil aviation systems are monitored. The analysis of the efficiency of the proposed approach to data processing showed the possibility of reducing operating costs, which can be considered within the framework of sustainable development of civil aviation. An important practical result is that the authors propose a Datahub model to facilitate the efficient collection, processing, and usage of aviation-related statistical data, supporting both sustainable decision-making and cost minimisation. A case study on aviation radio equipment demonstrates the application of statistical data processing techniques, incorporating the changepoint effect through Monte Carlo simulations
aDapT-XR: Adaptive Data Allocation and Prioritization for Synchronizing Real and Virtual Worlds in XR Digital Twins
Get PDFDigital Twins (DT) and Extended Reality (XR) technologies are leading the way in industry transformation by bridging the real and virtual worlds and enabling real-time user-digital system interaction and simulation. Despite their promise, XR-enabled DTs still face considerable difficulties in ensuring smooth synchronization between the actual and virtual worlds, especially in network-constrained scenarios. This paper addresses these challenges by introducing aDapT-XR (Adaptive Data Allocation and Prioritization Technique for DTs in eXtended Reality), a novel network-aware data prioritization framework designed for heterogeneous data flows in real-time XR environments. aDapT-XR dynamically adjusts data transmission priorities according to network conditions, reducing latency and improving quality of service (QoS) levels. This work addresses the main limitations of existing methodologies and contributes to the advancement of XR-DT system design by offering practical solutions for live shows, industrial monitoring, and remote collaboration
The Diplomacy of Uncertainty: Exploring the Protean Power of Aspirant States
Get PDFThis article examines how aspirant states with limited international recognition secure membership in international organisations. While soft and control power is a suitable framework to explore the foreign policy conduct of recognised states, in this article, we argue that aspirant states facing significant barriers to full recognition and membership in international organisations can leverage protean power, which involves adaptability, strategic innovation, and improvisation, to navigate complex political landscapes and achieve varying degrees of success in their pursuit of international legitimacy. We use Kosovo's diplomatic efforts as a case study, examining its successes and failures in joining organisations such as the World Customs Organization, the Permanent Court of Arbitration, and UNESCO. By comparing successful, partially successful, and unsuccessful cases, the article provides critical insights into the dynamics of international legitimacy, the politicisation of multilateral decision-making, and the evolving norms of state membership in a fragmented international order
Summary of Society of Actuaries in Ireland and Continuous Mortality Investigation Working Paper 199
Get PDFThe Society of Actuaries in Ireland (SAI) and the Continuous Mortality Investigation (CMI) of the Institute & Faculty of Actuaries (IFoA), UK have jointly completed an investigation into the experience of term assurances in Ireland over the period 2015-2021. The investigation considered, for term assurances sold on standard rates, the mortality experience for 2016-2021 and the accelerated critical illness and stand-alone critical illness experience for 2015-2021. Experience from 2015/2016-2019 was
considered in aggregate while experience for the pandemic years 2020 and 2021 was considered individually to allow assessment of the impact of the pandemic on experience. The SAI and CMI would like to thank the participating insurance companies who provided the data underlying this
investigation