National University of Ireland, Maynooth
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Data-driven profiles of attention-deficit/hyperactivity disorder using objective and ecological measures of attention, distractibility, and hyperactivity
Get PDFIn the past two decades, the traditional nosology of attention-deficit/hyperactivity disorder (ADHD) has been criticized for having insufficient discriminant validity. In line with current trends, in the present study, we combined a data-driven approach with the advantages of virtual reality aiming to identify novel behavioral profiles of ADHD based on ecological and performance-based measures of inattention, impulsivity, and hyperactivity. One hundred and ten Spanish-speaking participants (6–16 years) with ADHD (medication-naïve, n = 57) and typically developing participants (n = 53) completed AULA, a continuous performance test embedded in virtual reality. We performed hybrid hierarchical k-means clustering methods over the whole sample on the normalized t-scores of AULA main indices. A five-cluster structure was the most optimal solution. We did not replicate ADHD subtypes. Instead, we identified two clusters sharing clinical scores on attention indices, susceptibility to distraction, and head motor activity, but with opposing scores on mean reaction time and commission errors; two clusters with good performance; and one cluster with average scores but increased response variability and slow RT. DSM-5 subtypes cut across cluster profiles. Our results suggest that latency of response and response inhibition could serve to distinguish among ADHD subpopulations and guide neuropsychological interventions. Motor activity, in contrast, seems to be a common feature among ADHD subgroups. This study highlights the poor feasibility of categorical systems to parse ADHD heterogeneity and the added value of data-driven approaches and VR-based assessments to obtain an accurate characterization of cognitive functioning in individuals with and without ADHD
Green Machine Learning: Analysing the Energy Efficiency of Machine Learning Models
Get PDFThe consumption of energy by Machine Learning
(ML) has increased significantly. There is growing concern about
the sustainable use of ML, where choosing the best ML model
should also consider energy efficiency. The main objective of
the Green Machine Learning paradigm is the simultaneous
optimisation of accuracy and energy consumption. The literature
has presented some suggestions for metrics to be used. However, these metrics have not been extensively compared among
different ML models. To address this aspect, in this paper, we
have analysed six Machine Learning models applied to three
benchmark datasets for binary classification tasks, focusing on
performance and energy consumption. The results of the F1-
Score show that the random forests model outperformed the
other models, while logistic regression was more energy efficient.
These results demonstrate the trade-offs between model performance and energy consumption, providing valuable guidance
for algorithm selection. Performance metrics are an essential
benchmark, with Python’s Scikit-Learn suite of models often
outperforming neural networks in classification tasks. Future
research should extend energy analysis to other machine learning
methods and consider metrics that balance performance and
energy consumption
Revisiting excitation force estimation in WECs: On the (mis)use of structure-based estimation approaches
Get PDFWave excitation force (torque) estimators, vital in wave energy systems, generally combine the nominal
representation of a wave energy converter (WEC) with an excitation force (perturbation) model. Thus, this
model-based estimation approach, grounded in the internal model principle, often employs two perturbation
models: (i) the harmonic oscillator structure, prevalent in literature, assuming sinusoidal signals; and (ii) the
integrator (random walk) scheme, assuming unit step-like signals. These models comprehensively represent
a specific family of estimators, as discussed in this study. However, both models may struggle to capture
the irregular (stochastic) nature of ocean waves. This study challenges the prevailing assumption that the
harmonic oscillator structure, selected for its resemblance to ocean wave oscillations, is inherently the optimal
choice. This study provides a rigorous discussion on convergence conditions. Thus, is shown that, while the
harmonic oscillator can be highly effective under specific conditions, the random walk structure, despite
its simplicity, can surpass the performance of the harmonic oscillator scheme. Formal proofs support this
argument, emphasising the effectiveness of the harmonic oscillator can be guaranteed with periodic signals
On the Effective Implementation of Control Structures to Multi-DoF wave Energy Converters
Get PDFMaximising energy output through advanced control strategies is pivotal for the economic viability of wave
energy converters (WECs). However, most existing literature
primarily focuses on theoretical case studies, where WECs are
constrained to operate in a single degree of freedom (DoF).
This simplification is made due to the added complexity of
optimizing across multiple DoFs. In this study, we assess the
necessity of incorporating multiple DoFs within the control
framework, evaluating its effectiveness in a numerical simulation environment that replicates WEC performance across
multiple DoFs. To provide a basis for comparison, we contrast
the conventional PI controller with the innovative LiteCon
controller. Our study reveals two key findings: (i) Single DoF
control may suffice when the primary DoF of the power takeoff system is accurately identified, and (ii) the straightforward
LiteCon controller outperforms the traditional PI controller by
a significant margin
Historical trends of floating wind turbine fatigue loads (Ireland 1920–2010)
Get PDFWe present a new method for analysing the fatigue loads of offshore floating wind turbines over the long term. In this method, bias-corrected wind and wave data from the 20th century (ERA20C versus ERA5 reanalysis) is used for an energetic sea location in western Ireland. To reduce the computational cost and theoretical complexity, the sea states were clustered into categories to indicate how these categories evolve over three climate periods during a period of 30 years (1921–1950, 1951–1980, and 1981–2010). OpenFAST aeroelastic code simulation in floating mode was then conducted at each sea state for spar-type 5-MW and semi-submersible 15-MW wind turbines. This shows the damage loads and fatigue increments over the century, with some relevant cases (rotor torque, blade pitch and flapping, and tower side–side and fore–aft moments) showing fatigue increments of 5%–8%. Thus, in the new method, historical data are used to create a model to represent the evolution of sea states and corresponding fatigue over the long term, which can be applied globally to future projections
The Montessori school as a ‘healing’ environment: translating childhood trauma research into effective, trauma-informed, educational practice
Get PDFBackground: Childhood trauma/adversity is pervasive and has far-reaching consequences for
children’s health and well-being, leading to increased calls for trauma-informed practice (TIP).
Archival data show that early Montessori schools (circa 1907-1917) were recognised as ‘healing’ schools, wherein trauma-affected children improved dramatically.
Aims/objectives: This project aimed to (1) investigate claims of psychological healing in early
Montessori schools; (2) integrate the findings with contemporary knowledge on TIP; (3)
develop a novel Continuing Professional Development (CPD) programme based on this integration; and (4) evaluate its perceived impact on staff in a test school.
Method: A multi-method, three-strand approach was used comprising three distinct and
sequential studies. Study 1 involved a documentary analysis of eyewitness testimonies, media reports, and Montessori’s own accounts of her early schools, to investigate how the Montessori approach supported trauma-affected children. Study 2 integrated the findings of Study 1 with
contemporary trauma literature to develop an innovative CPD programme designed to enhance the capacities of early childhood teachers to support trauma-affected children. Study 3 then
used a case study approach to provide a rich contextual account of teachers’ (n=11) experiences of engaging with this programme, focusing on its perceived impact on their knowledge,
attitudes/beliefs, professional practice, and their views on its feasibility.
Findings: Study 1 identified significant evidence of psychological healing in trauma-affected
children attending Montessori’s early schools. Study 2 found that several features of
Montessori education cohere with contemporary research on TIP approaches, especially the Neurosequential Model in Education (NME), and that these can be integrated to develop a programmme of Montessori-attuned TIP. Study 3 found that early childhood/Montessori teachers rated the new programme highly, stating it positively impacted their practice.
Conclusion: This project makes a significant original contribution to existing knowledge on
Montessori pedagogy and TIP and has important implications for supporting trauma-affected
children in Ireland and elsewhere
Climate Justice and the University. Shaping a Hopeful Future for All.
Get PDFA radical exploration of how higher education can advance transformative climate justice.
Amid the worsening climate crisis and intensifying inequities, higher education can play a powerful role in addressing the intersecting crises facing humanity. Institutions of higher education hold untapped potential to advance social justice and reduce climate injustices. However, universities are not yet structured to accelerate social change for the public good. In Climate Justice and the University, Jennie Stephens reimagines the potential of higher education to advance human well-being and promote ecological health.
Drawing on over thirty years of experience working on the climate crisis within higher education, Stephens offers a provocative and pathbreaking vision of how higher education can accelerate the shift toward more equitable, healthy, and stable futures for all. Building on a US and European context, she integrates examples from the innovative landscape of transformative education initiatives around the world.
With climate chaos exacerbating instability of all kinds, reimagining the transformative power of higher education is hopeful and empowering. By inviting readers to collectively reimagine different priorities and structures within higher education, Stephens disrupts long-held assumptions about how universities advance learning and research, suggesting possibilities to shape a more equitable future for all
Is there a nationality wage premium in European football?
Get PDFWe investigate the presence of nationality salary premia in two top European football leagues (the Premier League
and Serie A). We uncover a substantial pay premium for South American players (primarily driven by Argentina
and Brazil) of between 11 and 15 per cent in magnitude. We investigate possible mechanisms, such as whether
these salary effects are driven by new entrants to the league, and whether they are reflected in team attendances
and team performance. Fans appear to respond to higher proportions of South American players in England, but
not in Italy. We discuss the implications of these results and suggest why potential differences might exist across
the leagues
Social Media, Newsworthiness, and Missing White Woman Syndrome: A Criminological Analysis
Get PDFMissing White Woman Syndrome has been widely acknowledged within traditional mainstream media, resulting in a heavy focus on missing white women and a simultaneous underrepresentation of missing women from minority ethnic communities. However, less is known about whether this has carried through to social media, wherein users play a key role in determining what becomes widespread news. This review seeks to examine this issue with reference to existing research. It begins by exploring the concept of newsworthiness and the ways in which social media influences the distribution of news. It will then review the concept of the ‘ideal victim’, and its continued association with ethnicity. Finally, the review will examine Missing White Woman Syndrome and the ways in which it has historically manifested within traditional media and continues to manifest on social media. The review will conclude with a discussion on findings and avenues for future research in Ireland and internationally
