Dublin City University
  • Dublin, Ireland
Recent publications
The COVID-19 pandemic has caused a great “reset” and has challenged many assumptions about work and life in general. Our focus in this paper is on the future of global work in the context of multinational enterprises (MNEs). We take a phenomenon-based approach to describe the important trends and challenges affecting the where, who, how and why of global work. As we highlight implications for organizations and individuals, we offer a set of research questions to guide future research and inform IHRM practitioners.
Sub-Saharan Africa (SSA) was colonised for about a century by the British, French and other European countries. Therefore, we examine these forms of colonisation on accounting development in Africa. We use a description-explanatory approach to show how three forms of colonisation have driven the development of accounting in Africa during and post-colonisation era. This paper defines driving forces during the colonisation period as ex-ante driving forces, and after independence, as ex-post driving forces. We identify among the ex-ante driving forces, governance, economic policy, education and language influenced accounting systems/practices, and they are still predominant. Regarding the ex-post, we found four ex-post driving forces that impact accounting in SSA, which supports the instrumental form of accounting colonisation. These four driving forces are foreign aid, foreign trade liberalisation, membership in international associations and prevalence of foreign ownership. This paper provides insights into how accounting practices have evolved in Africa and how colonisation has driven different accounting systems across the continent. Unlike prior studies, which are limited to pre or post-colonial eras, we provide an understanding of accounting development during the colonial and post-colonial era. Therefore, we demonstrate how colonisation still influences accounting development even after independence in many African countries.
Development of scientific literacy is a crucial aim of science education across the globe and research suggests that this can be realized through student exploration of socioscientific issues. While the COVID-19 crisis, emergency school closures and restrictions to in-class teaching, had negative impacts on teaching and on student learning and wellbeing, it also presents an opportunity to explore authentic socioscientific issues. This research explores teachers’ perspectives on addressing the COVID-19 crisis as socioscientific issues in secondary science education. This qualitative study surveyed 266 Irish secondary school science teachers about their experiences during the COVID-19 crisis. Thematic analysis was used to identify the reasons why teachers did and did not address the COVID-19 crisis as SSI. These findings were triangulated with findings from follow-up interviews. The majority of teachers in this study addressed the COVID-19 crisis as SSI. The COVID-19 crisis was explored within the curriculum, through project work and research, and through classroom discussion. Teachers described four barriers to exploring the COVID-19 crisis with their students: The COVID-19 crisis was not part of the curriculum; The lack of F2F contact made judging students’ reactions challenging; There was already too much focus on the COVID-19 crisis in everyday life and concerns over student wellbeing while discussing the sensitive topic of the COVID-19 crisis. Teachers noted that addressing the COVID-19 crisis led to benefits to student learning, health, wellbeing and hygiene.
Aging is a natural process in organisms with its underlying mechanisms remaining unknown. Brain aging is accompanied by cognitive deficits and movement disorders, which signify the importance of elaborating its main mechanisms. In this study, oxidative stress biomarkers for lipid peroxidation and thiol redox state were assessed in different brain areas in male mice, categorised in respect to aging as young (three months), middle (eleven months) and elder aged (twenty-three months). Senescence was associated with an increase of lipid peroxidation and a decrease of reduced and oxidized glutathione. In some brain areas, reduced cysteine and oxidized protein thiols were increased with aging. Results support the theory that aging is associated with oxidative stress in the brain of mice and provide an insight in the biochemical aspect of aging in reference to thiol redox status as a potential marker for aging.
This study aims to numerically investigate the effects of geometric designs of tubes and shell on thermal performance enhancement of latent thermal energy storage system (LTESS). Stearic acid is used as a phase change material (PCM) while water acts as heat transfer fluid (HTF). Starting with a base case consisting of three circular HTF tubes within a circular shell, the tube and shell geometries are modified systematically. First, the effect of tube shapes and their orientations are investigated in detail. The circular exteriors of HTF tubes are modified with hexagonal, pentagonal, square and triangular shapes. The performance of triangular tubes with the vertex pointing downward exceeds all the other tube configurations. It augments the melting rate of the PCM by 27.2% and the energy storage capacity of the LTESS by 3.72%, as compared to the base case. The bottom vertex angle of the best HTF tube design is then varied yielding 45 • as the optimum triangular tube configuration. It improves the energy storage capability of the LTESS by 7.61% and the melting rate of the PCM by 41.4%. Following the optimum HTF tube design, the triangulated shell designs with various bottom vertex angles are explored. The 75 • bottom vertex angle of the shell offers maximum improvement. It accelerates the melting rate of the PCM by 66.9% while enhancing the energy storage capacity of the LTESS by 23.7% in comparison to the base case. Lastly, two new correlations of melting Fourier number and average Nusselt number are proposed for the optimum LTESS design configuration.
Metal complex luminophores have seen dramatic expansion in application as imaging probes over the past decade. This has been enabled by growing understanding of methods to promote their cell permeation and intracellular targeting. Amongst the successful approaches that have been applied in this regard is peptide-facilitated delivery. Cell-permeating or signal peptides can be readily conjugated to metal complex luminophores and have shown excellent response in carrying such cargo through the cell membrane. In this article, we describe the rationale behind applying metal complexes as probes and sensors in cell imaging and outline the advantages to be gained by applying peptides as the carrier for complex luminophores. We describe some of the progress that has been made in applying peptides in metal complex peptide-driven conjugates as a strategy for cell permeation and targeting of transition metal luminophores. Finally, we provide key examples of their application and outline areas for future progress.
Co-authored by a Computer Scientist and a Digital Humanist, this article examines the challenges faced by cultural heritage institutions in the digital age, which have led to the closure of the vast majority of born-digital archival collections. It focuses particularly on cultural organizations such as libraries, museums and archives, used by historians, literary scholars and other Humanities scholars. Most born-digital records held by cultural organizations are inaccessible due to privacy, copyright, commercial and technical issues. Even when born-digital data are publicly available (as in the case of web archives), users often need to physically travel to repositories such as the British Library or the Bibliothèque Nationale de France to consult web pages. Provided with enough sample data from which to learn and train their models, AI, and more specifically machine learning algorithms, offer the opportunity to improve and ease the access to digital archives by learning to perform complex human tasks. These vary from providing intelligent support for searching the archives to automate tedious and time-consuming tasks. In this article, we focus on sensitivity review as a practical solution to unlock digital archives that would allow archival institutions to make non-sensitive information available. This promise to make archives more accessible does not come free of warnings for potential pitfalls and risks: inherent errors, "black box" approaches that make the algorithm inscrutable, and risks related to bias, fake, or partial information. Our central argument is that AI can deliver its promise to make digital archival collections more accessible, but it also creates new challenges - particularly in terms of ethics. In the conclusion, we insist on the importance of fairness, accountability and transparency in the process of making digital archives more accessible.
Background/objective Negative emotional states, such as depression, anxiety, and stress challenge health care due to their long-term consequences for mental disorders. Accumulating evidence indicates that regular physical activity (PA) can positively influence negative emotional states. Among possible candidates, resilience and exercise tolerance in particular have the potential to partly explain the positive effects of PA on negative emotional states. Thus, the aim of this study was to investigate the association between PA and negative emotional states, and further determine the mediating effects of exercise tolerance and resilience in such a relationship. Method In total, 1117 Chinese college students (50.4% female, Mage=18.90, SD=1.25) completed a psychosocial battery, including the 21-item Depression Anxiety Stress Scale (DASS-21), the Connor-Davidson Resilience Scale (CD-RISC), the Preference for and Tolerance of the Intensity of Exercise Questionnaire (PRETIE-Q), and the International Physical Activity Questionnaire short form (IPAQ-SF). Regression analysis was used to identify the serial multiple mediation, controlling for gender, age and BMI. Results PA, exercise intensity-tolerance, and resilience were significantly negatively correlated with negative emotional states (Ps<.05). Further, exercise tolerance and resilience partially mediated the relationship between PA and negative emotional states. Conclusions Resilience and exercise intensity-tolerance can be achieved through regularly engaging in PA, and these newly observed variables play critical roles in prevention of mental illnesses, especially college students who face various challenges. Recommended amount of PA should be incorporated into curriculum or sport clubs within a campus environment.
A finite difference method is constructed to solve singularly perturbed convection-diffusion problems posed on smooth domains. Constraints are imposed on the data so that only regular exponential boundary layers appear in the solution. A domain decomposition method is used, which uses a rectangular grid outside the boundary layer and a Shishkin mesh, aligned to the curvature of the outflow boundary, near the boundary layer. Numerical results are presented to demonstrate the effectiveness of the proposed numerical algorithm.
Ancient philosophy proposed a wide range of possible approaches to life which may enhance well-being. Stoic philosophy has influenced various therapeutic traditions. Individuals today may adopt an approach to life representing a naive Stoic Ideology, which nevertheless reflects a misinterpretation of stoic philosophy. How do these interpretations affect well-being and meaning in life? We examine the differential effects of Stoic Ideology on eudaimonic versus hedonic well-being across three cultural contexts. In this pre-registered study, across samples in New Zealand ( N = 636), Norway ( N = 290), and the US ( N = 381) we found that a) Stoic Ideology can be measured across all three contexts and b) Converging evidence that Stoic Ideology was negatively related to both hedonic well-being and eudaimonic well-being. Focusing on specific relationships, we found especially pronounced effects for Taciturnity (the desire to not express emotions) and Serenity (the desire to feel less emotions). Despite being a misinterpretation of stoic philosophy, these findings highlight the important role of individuals’ orientations to emotional processing for well-being.
Aligning to the 2030 United Nations Sustainable Development Goal (SDGs) 12, we investigate the role of renewable energy in achieving sustainable consumption and production pattern in Africa. This study addresses the question: whether the use of renewable energy helps achieve production and consumption patterns free from environmental degradation? We use panel data on 14 African countries from 2002 to 2014 and a robust econometric approach such as panel corrected standard error (PSCE), instrumental generalized method of moment (IV-GMM), and quantile regressions. We find that (1) renewable energy consumption helped to achieve a consumption and production pattern that is free from environmental degradation; (2) there is a significant positive heterogeneous effect of renewable energy consumption on sustainable consumption and production pattern, but the impact level dropped in the long-run. In light of this, we recommend that African countries invest in green energy to achieve sustainable production and consumption patterns
Homeless service users were screened for autism spectrum disorder through one of Ireland’s leading not for profit service providers. Keyworkers acted as proxy informants; their caseloads were screened using the DSM-5—Autistic Traits in the Homeless Interview (DATHI). Client current and historical health and behaviour data was collated. A representative sample of 106 eligible keyworkers caseloads were screened, identifying 3% “present” and 9% “possibly present” for autistic traits with the DATHI. These findings suggest a high estimate of autism prevalence and support emerging evidence that, people with autism are overrepresented in the homeless population, compared to housed populations. Autism may be a risk factor for entry into homelessness and a challenge to exiting homeless and engaging with relevant services.
Breast cancers (BrCas) that overexpress oncogenic tyrosine kinase receptor HER2 are treated with HER2-targeting antibodies (such as trastuzumab) or small-molecule kinase inhibitors (such as lapatinib). However, most patients with metastatic HER2 ⁺ BrCa have intrinsic resistance and nearly all eventually become resistant to HER2-targeting therapy. Resistance to HER2-targeting drugs frequently involves transcriptional reprogramming associated with constitutive activation of different signaling pathways. We have investigated the role of CDK8/19 Mediator kinase, a regulator of transcriptional reprogramming, in the response of HER2 ⁺ BrCa to HER2-targeting drugs. CDK8 was in the top 1% of all genes ranked by correlation with shorter relapse-free survival among treated HER2 ⁺ BrCa patients. Selective CDK8/19 inhibitors (senexin B and SNX631) showed synergistic interactions with lapatinib and trastuzumab in a panel of HER2 ⁺ BrCa cell lines, overcoming and preventing resistance to HER2-targeting drugs. The synergistic effects were mediated in part through the PI3K/AKT/mTOR pathway and reduced by PI3K inhibition. Combination of HER2- and CDK8/19-targeting agents inhibited STAT1 and STAT3 phosphorylation at S727 and up-regulated tumor suppressor BTG2. The growth of xenograft tumors formed by lapatinib-sensitive or -resistant HER2 ⁺ breast cancer cells was partially inhibited by SNX631 alone and strongly suppressed by the combination of SNX631 and lapatinib, overcoming lapatinib resistance. These effects were associated with decreased tumor cell proliferation and altered recruitment of stromal components to the xenograft tumors. These results suggest potential clinical benefit of combining HER2- and CDK8/19-targeting drugs in the treatment of metastatic HER2 ⁺ BrCa.
Purpose Low-grade glioma (LGG) patients may face health-related quality-of-life (HRQoL) impairments, due to the tumour, treatment and associated side-effects and prospects of progression. We systematically identified quantitative studies assessing HRQoL in adult LGG patients, for: aspects of HRQoL impacted; comparisons with non-cancer controls (NCC) and other groups; temporal trends; and factors associated with HRQoL. Methods MEDLINE, CINAHL, Embase, PubMed, and PsycINFO were systematically searched from inception to 14th September 2021. Following independent screening of titles and abstracts and full-texts, population and study characteristics, and HRQoL findings were abstracted from eligible papers, and quality appraised. Narrative synthesis was conducted. Results Twenty-nine papers reporting 22 studies (cross-sectional, n = 13; longitudinal, n = 9) were identified. Papers were largely good quality, though many excluded patients with cognitive and communication impairments. Comparators included high-grade gliomas (HGG) ( n = 7); NCCs ( n = 6) and other patient groups ( n = 3). Nineteen factors, primarily treatment (n = 8), were examined for association with HRQoL. There was substantial heterogeneity in HRQoL instruments used, factors and aspects of HRQoL assessed and measurement timepoints. HRQoL, primarily cognitive functioning and fatigue, in adult LGG patients is poor, and worse than in NCCs, though better than in HGG patients. Over time, HRQoL remained low, but stable. Epilepsy/seizure burden was most consistently associated with worse HRQoL. Conclusion LGG patients experience wide-ranging HRQoL impairments. HRQoL in those with cognitive and communication impairments requires further investigation. These findings may help clinicians recognise current supportive care needs and inform types and timings of support needed, as well as inform future interventions.
In general, solving fractional partial differential equations either numerically or analytically is a difficult task. However, mathematicians have tried their best to make the task easy and promoted various techniques for their solutions. In this regard, a very prominent and accurate technique, which is known as the new technique of the Adomian decomposition method, is developed and presented for the solution of the initial-boundary value problem of the diffusion equation with fractional view analysis. The suggested model is an important mathematical model to study the behavior of degrees of memory in diffusing materials. Some important results for the given model at different fractional orders of the derivatives are achieved. Graphs show the obtained results to confirm the accuracy and validity of the suggested technique. These results are in good contact with the physical dynamics of the targeted problems. The obtained results for both fractional and integer orders problems are explained through graphs and tables. Tables and graphs support the physical behavior of each problem and the best of physical analysis. From the results, it is concluded that as the fractional order derivative is changed, the graphs or paths of dynamics are also changed. Therefore, we now choose the best solution or dynamic of the problem at a particular derivative order. It is analyzed that the present technique is one of the best techniques to handle the solutions of fractional partial differential equations having initial and boundary conditions (BCs), which are very rare in literature. Furthermore, a small number of calculations are done to achieve a very high rate of convergence, which is the novelty of the present research work. The proposed method provides the series solution with twice recursive formulae to increase the desired accuracy and is preferred among the best techniques to find the solution of fractional partial differential equations with mixed initials and BCs.
Background: Malaria is curable. Nonetheless, over 229 million cases of malaria were recorded in 2019, along with 409,000 deaths. Although over 42 million Brazilians are at risk of contracting malaria, 99% percent of all malaria cases in Brazil are located in or around the Amazon rainforest. Despite declining cases and deaths, malaria remains a major public health issue in Brazil. Accurate spatiotemporal prediction of malaria propagation may enable improved resource allocation to support efforts to eradicate the disease. Methods: In response to calls for novel research on malaria elimination strategies that suit local conditions, in this study, we propose machine learning (ML) and deep learning (DL) models to predict the probability of malaria cases in the state of Amazonas. Using a dataset of approximately 6 million records (January 2003 to December 2018), we applied k-means clustering to group cities based on their similarity of malaria incidence. We evaluated random forest, long-short term memory (LSTM) and dated recurrent unit (GRU) models and compared their performance. Results: The LSTM architecture achieved better performance in clusters with less variability in the number of cases, whereas the GRU presents better results in clusters with high variability. Although Diebold-Mariano testing suggested that both the LSTM and GRU performed comparably, GRU can be trained significantly faster, which could prove advantageous in practice. Conclusions: All models showed satisfactory accuracy and strong performance in predicting new cases of malaria, and each could serve as a supplemental tool to support regional policies and strategies.
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12,059 members
Prince Anandarajah
  • School of Electronic Engineering
Bert Gordijn
  • Institute of Ethics
Sithara Pavithran Sreenilayam
  • Advanced Processing Technology Research Centre (APT)
Conor McArdle
  • School of Electronic Engineering
Glasnevin, 9, Dublin, Ireland
Head of institution
Prof. Daire Keogh