National University of Ireland, Maynooth
MURAL - Maynooth University Research Archive LibraryNot a member yet
18981 research outputs found
Sort by
Cognitive Profile of ADHD in Older Adults: A Systematic Review
Full text linkObjectives:
ADHD is now recognized as a common condition in adulthood, but the evidence supporting a separate characterization of a cognitive profile for ADHD in older adults is scarce. Consequently, the goal of the current study was to conduct a systematic review that helps clarify the cognitive characteristics of ADHD in older individuals.
Method:
We conducted a systematic review with narrative synthesis, considering studies on older adults with ADHD and research on cognitive domains involved in adults 50 years old and older with a confirmed diagnosis of ADHD, in three electronic databases (PubMed, Web of Science, and Embase). Ten studies (3 longitudinal and 7 cross-sectional) with clearly separated cognitive data for older adults with ADHD were included in this review.
Results:
Results showed an overall worse performance in attention and episodic memory for older adults with ADHD compared to their younger counterparts and older healthy controls. Evidence concerning executive functions was mixed, with some studies showing a worse performance in working memory compared to older healthy controls, but with other studies showing a similar or even better performance than younger adults with ADHD.
Conclusions:
A cognitive characterization of ADHD in older adults requires further research to clarify whether it can be considered a separate entity and how to establish a differential diagnosis with other age-related conditions. Moreover, there is a need for internationally agreed common neuropsychological assessment protocols that set boundaries between younger and older adults with ADHD
When LLMs Annotate: Reliability Challenges in Low-Resource NLI
Full text linkThis paper systematically evaluates LLM reliability on the complex semantic task of Natural Language Inference (NLI) in Farsi, assessing six prominent models across eight prompt
variations through a multi-dimensional framework that measures accuracy, prompt sensitivity, and intra-class consistency. Our results
demonstrate that prompt design-particularly the
order of premise and hypothesis-significantly
impacts prediction stability. Proprietary models
(Claude-Opus-4, GPT-4o) exhibit superior stability and accuracy compared to open-weight
alternatives. Across all models, the ’Neutral’
class emerges as the most challenging and least
stable category. Crucially, we redefine model
instability as a diagnostic tool for benchmark
quality, demonstrating that observed disagreement often reflects valid challenges to ambiguous or erroneous gold-standard labels
Data fusion for low-cost sensors: A systematic literature review
Full text linkData fusion (DF) addresses the challenge of integrating heterogeneous data sources to improve decision-making and inference. Although DF has been widely explored, no prior systematic review has specifically focused on its application to low-cost sensor (LCS) data in environmental monitoring. To address this gap, we conduct a systematic literature review (SLR) following the PRISMA framework, synthesising findings from 82 peer-reviewed articles. The review addresses three key questions: (1) What fusion methodologies are employed in conjunction with LCS data? (2) In what environmental contexts are these methods applied? (3) What are the methodological challenges and research gaps? Our analysis reveals that geostatistical and machine learning approaches dominate current practice, with air quality monitoring emerging as the primary application domain. Additionally, artificial intelligence (AI)-based methods are increasingly used to integrate spatial, temporal, and multimodal data. However, limitations persist in uncertainty quantification, validation standards, and the generalisability of fusion frameworks. This review provides a comprehensive synthesis of current techniques and outlines key directions for future research, including the development of robust, uncertainty-aware fusion methods and broader application to less-studied environmental variables
Adam Simpson: becoming an illustrator
Full text linkThis article explores the work of illustrator Adam Simpson, whose practice encompasses both commissioned and self-initiated projects, most recently exemplified through a collaboration with the Royal Mail in the UK
On Kierkegaard’s Side: Re-situating Henri de Lubac’s Theology amid the Non-humanist Turn in France
Full text linkThis chapter explores the significant ways in which de Lubac’s (1896–1991) theological reception of Kierkegaard informed his stance toward humanism. By surveying the default position of negative anthropology in the historiography of the nonhumanist turn in French thought, the chapter locates de Lubac at the center of the debate and observes that de Lubac’s reception of Kierkegaard is neglected, and as a result, scholars wrongly try to conform his views to that of Nietzsche or Heidegger. To identify the origin of this interpretive trajectory, the chapter revisits and evaluates Maurice Blanchot’s critical review of de Lubac’s The Drama of Atheist Humanism (1945), entitled “On Nietzsche’s Side” (1946). Furthermore, the chapter argues that to avoid conflating de Lubac’s theological anthropology with a nonhumanist inheritance, one must not ignore his treatment of Kierkegaard. The chapter re-establishes the link between de Lubac’s correspondence network and his engagement with Kierkegaard studies to suggest that de Lubac’s interest in Kierkegaard was not ornamental but rather fundamental to his ressourcement project. Like this, the chapter recovers the Kierkegaardian inheritance of de Lubac’s Christian humanism that transformed Catholic theology in the twentieth century
Empowering Education for Sustainable Development: A Submission from the BEST Network for Ireland’s Third SDG National Implementation Plan - A Case for a Bioeconomy Approach
Full text linkThis submission from the Bioeconomy Education and Sustainability Teachers (BEST) Network contributes to the public consultation on Ireland’s Third Sustainable Development Goals (SDGs) National Implementation Plan (NIP). It positions Education for Sustainable Development (ESD), aligned with SDG Target 4.7, as a central delivery mechanism for achieving Ireland’s SDG commitments. The submission makes the case for embedding a bioeconomy approach across education systems to support systems thinking, circularity, ecological limits and a just transition. It highlights gaps in current curriculum integration, educator capacity and coordination across policy frameworks. Key recommendations include national leadership for SDG education, sustained funding and formal integration of bioeconomy competencies from early years through higher and adult education. The submission emphasises the critical role of initial teacher education and continuing professional development. It also calls for meaningful youth participation and whole-school and community-based approaches. Finally, it recommends education-specific SDG indicators and reporting to ensure measurable impact. Collectively, these actions would embed education as a core pillar of Ireland’s sustainable development strategy
Deriving Gridded Soil Moisture Estimates Using Earth Observation Data and a Process Informed Statistical Machine Learning Approach
Full text linkSoil moisture is classified as an essential climate variable (ECV) and is relevant to understanding hydrological, agricultural and ecological processes. Yet, in spite of its importance, direct observations of soil moisture remain limited globally—those that exist are typically limited in duration and spatial extent. Consequently, alternative approaches for estimating soil moisture have been developed, including water balance (‘bucket’) models, the use of remotely sensed information and the application of land surface modelling techniques. Spaceborne and land surface modelling based methods offer significant potential for monitoring and modelling soil moisture at a variety of spatial scales; however, their resolution remains relatively coarse for global and continental scale applications. At country scale, land surface models have demonstrated their potential but they require access to computational resources to deliver high resolution products. With the advent of machine‐ and deep‐ learning and data fusion techniques, high resolution global and regional soil moisture datasets are increasingly becoming available. Here, we evaluated a statistical machine learning approach to downscale the European Space Agency's (ESA) Climate Change Initiative (CCI) combined passive and active soil moisture product for Ireland using covariates that included both static (e.g., topography) and dynamic (e.g., gridded rainfall and temperature) variables. The model was developed using in situ cosmic ray neutron sensor (CRNS) measurements obtained from a network of sites in the United Kingdom, justified on the basis that the United Kingdom is geographically similar to Ireland in terms of its climate, soil types and land cover management practices. The model was found to perform reasonably well when validated against limited in situ data obtained from available time domain reflectometry (TDR) measurements available from Ireland. The developed model was subsequently used to derive spatial estimates of soil moisture on a 1 km grid across the Republic of Ireland
Reliability-driven health-aware control augmentation strategies for wave energy converters
Full text linkEnergy-maximising controllers for wave energy converters (WECs) typically exaggerate device motion, which
can shorten device longevity and increase operational expenses (OpEx) by reducing maintenance intervals
and system reliability. This paper proposes a novel health-aware WEC control structure based on control
augmentation to achieve a suitable trade-off between energy maximisation and power take-off (PTO) lifetime
enhancement, ultimately leading to a lower levelised cost of energy (LCoE). The main advantage of implementing health-aware WEC control through control augmentation is that the proposed health-aware control
paradigm exhibits versatility regarding the selection of the nominal (energy-maximising) controller, enabling
the selection from a plethora of existing energy-maximising WEC controllers in the literature. Furthermore,
two distinct health-aware control augmentation strategies, feedforward and feedback, are proposed, along with
analytical derivations of the feasible ranges for their respective augmentation (tuning) parameters. Simulation
results demonstrate the versatility of the proposed health-aware control framework when applied with different
nominal WEC controllers. Furthermore, a comparative analysis is presented, identifying combinations of
augmentation strategies and nominal WEC controllers that yield appealing performance, in terms of lifetime
enhancement
Modelling and optimal control of tidal barrages: A moment-based approach
Full text linkTidal barrages generate electrical energy using the tidal height variations throughout the day, and stand out
from other renewable energy schemes because of their inherent storage capabilities and the relatively slow
variation of the tides, allowing flexibility in their operation. The resulting optimal control problem of operating
tidal barrages has unique features that call for a range of possible operating modes (generating, sluicing and
pumping). This paper presents a comprehensive model for tidal barrage power plants, using the La Rance
power plant as case study. The operation of the hydraulic turbines is modelled using a generic hill chart, which
accounts for all possible operating points (not only those with maximum efficiency, as commonly seen in the
literature). An artificial neural network was designed and trained to obtain a compact function approximation
for the hill chart. The optimal control problem is solved using moment-based control, a mathematical tool
from the family of weighted residual methods, broadly applied in wave energy control. Moment-based control
is implemented by parameterising the external and control inputs with a harmonic expansion, and the nature
of the frequency range required for an efficient parameterisation is explored
Contemporaneity with Christ: Cornelio Fabro’s Kierkegaardian Approach to the Mystical Writings of St. Gemma Galgani
Full text linkThe Italian priest-philosopher and Kierkegaard scholar Fr. Cornelio Fabro (1911–1995) published a monograph on the mystical experiences of Gemma Galgani (1878–1903), and interpreted Gemma’s testimony using a Kierkegaardian motif. This chapter shows that for Fabro, Kierkegaard’s notion of “contemporaneity with Christ” (i) in general, can be given content with the lives of the saints as concrete examples of the intensification of Christian existence; and (ii) in particular, can be used as an interpretive lens to make sense of Gemma Galgani’s mystical experience of the stigmata as supernatural testimony