Digital Commons Network^™

Plant-Herbivore Interactions In A Changing Climate And Implications For Seagrass Resilience, Caitlyn M. O'Dea

Theses: Doctorates and Masters

Climate change is affecting herbivore distributions and abundance, resulting in intensified grazing pressure on foundation species such as seagrasses. This, coupled with other, rapid changes in estuarine ecosystems, may threaten the resilience of seagrass. While the overall resilience of seagrasses is generally well-studied, the timeframes of recovery have received comparatively little attention, particularly in temperate estuaries. This study investigated the recovery time of two colonising seagrasses (Halophila ovalis and Ruppia megacarpa) following various intensities of simulated grazing in two southwestern Australian estuaries. Simulated grazing treatments (25%, 50%, 75%, and 100% removal from 1 m2 plots) were applied in field experiments …

The Concept And Role Of Meaningful Work In The Context Of Pakistan – An Exploratory Study Of Junior Doctors, Abid Hussain

Theses: Doctorates and Masters

Over the past decade, the concept of meaningful work has gained increased attention from human resource management, organisational science, and management scholars. This can be largely attributed to the growing global concern for the wellbeing and meaningful engagement of individuals in the workforce, especially since the COVID-19 pandemic. The literature on meaningful work reveals that there are multiple perspectives and theoretical approaches to the conceptualisation of meaningful work which can be found primarily within Western societies and Western scholarship and are often based on Western worldviews. Most of the quantitative and qualitative empirical studies adopt a reductionist approach and tend …

Carbon Geosequestration And Enhanced Oil Recovery In Geological Formations: Multi-Scale Analysis, Auby Baban

Theses: Doctorates and Masters

Carbon geosequestration (CGS) has been recognized as a strategic solution to prevent/counter the catastrophic consequences of climate change. However, despite recent cutting-edge technical research, predicting quantitative CO2 trapping in geological formations via capillary trapping is currently scarce. Moreover, several aspects of multiphase flow characteristics of CO2/brine/rock systems, that greatly impact carbon capture and containment security, require further investigations. Furthermore, combining carbon geosequestration with Enhanced Oil Recovery (EOR) is an efficient and economically attractive technology to reduce global warming caused by emissions of anthropologic CO2 from the combustion of fossil fuels, whereby it offsets some of the costs of CO2 extraction. …

Mass Spectrometry-Based Proteomic Analysis To Characterise Barley Breeding Lines, Mahya Bahmani

Theses: Doctorates and Masters

Barley is a key ingredient in the malting and brewing industry, and it is the fourth most important crop being cultivated worldwide. The protein content of the barley grain is one of the main components determining the quality and nutritive value of the food and beverages prepared from barley. Mass spectrometry-based proteomic analysis is a valuable tool that can guide and inform plant breeding strategies and crop improvement programs. Understanding the proteome changes in barley grain under different growing locations, the impact of different environmental conditions and its relationship with malting characteristics have the potential to inform breeding programs to …

Food Standards Agency, London (2023) Estimating Financial Cost To Individuals With A Food Hypersensitivity Project Report., Ciara Walsh

Research Outputs: 2025-Present

The Food Standards Agency (FSA) is a non-ministerial government department within the United Kingdom responsible for protecting public health and protecting consumer interests in relation to food in England, Wales, and Northern Ireland. Food Hypersensitivities (FHS) is a key priority within the FSA as it is an important food-related health issue with a severe and enduring impact for people living with it. FHS includes individuals living with a food allergy, coeliac disease and food intolerance.It is the responsibility of the FSA to seek ways to understand and reduce avoidable deaths, the negative impact of FHS on both consumers and businesses, …

Pattern And Polarization Diversity Multisector Annular Antenna For Iot Applications, Abel Zandamela, Nicola Marchetti, Max Ammann, Adam Narbudowicz, Wroclaw University Of Science And Technology

Articles

This work proposes a small pattern and polarization diversity multisector annular antenna with electrical size and profile of ka=1.2 and 0.018λ, respectively. The antenna is planar and comprises annular sectors that are fed using different ports to enable digital beamforming techniques, with efficiency and gain of up to 78%and 4.62 dBi, respectively. The cavity model analysis is used to describe the design concept and the antenna diversity. The proposed method can produce different polarization states (e.g., linearly and circularly polarized patterns) and pattern diversity characteristics covering the elevation plane. Owing to its small electrical size, low-profile and diversity properties, the …

Adolescent Overweight And Obesity In Ireland—Trends And Sociodemographic Associations Between 1990 And 2020, Aoibhín Moore Heslin, Aisling O'Donnell, Laura Kehoe, Janette Walton, Albert Flynn, John Kearney, Breige Mcnulty

Articles

Background: Overweight and obesity in adolescence is a growing issue and can have a range of both short- and long-term consequences on health.

Objectives: To analyse trends in adolescent weight status in Ireland across a 30-year period and to examine the influence of sociodemographic factors on overweight/obesity in Irish adolescents over time.

Methods: Body composition and body mass index weight status of Irish adolescents were compared using data from three nationally representative, cross-sectional Irish national food consumption surveys from 1990, 2006 and 2020. Adjusted analysis of associations between socio-demographic factors with the risk of adolescent overweight/obesity at each time point …

A Qualitative Analysis Of Women's Postnatal Experiences Of Breastfeeding Supports During The Perinatal Period In Ireland, Niamh Lawlor, Lucia Prihodova, Deborah Byrne, Megan Etherton, Felicienne Rahill, Catie Wilson, Elizabeth J. O'Sullivan

Articles

Ireland has among the lowest rates of breastfeeding worldwide. Despite policies to support breastfeeding, breastfeeding initiation and exclusivity remain low in Ireland. Greater knowledge about support received in the maternity unit may—in part—shed light on why this is so. Our aim was to analyse women's experiences of the breastfeeding supports available in the early postnatal period in Ireland. We conducted an analysis of an open-ended question on a cross-sectional survey about breastfeeding support conducted in the Republic of Ireland in 2022. Participants were asked to provide comments about the breastfeeding support they received in the maternity unit or during your …

Development Of Holographic Recording Material For Fabrication Of Solar Concentrators For Micro Satellites, Brian Rogers

Doctoral

Holographic solar concentration has been a topic of increasing interest over recent years because of the lightweight and physically compact nature of holograms, which gives them an advantage over other, conventional concentration methods. As holographic recording materials develop further, their characteristics prove to meet the demands required of them to make more effective holographic solar concentrators. The development of photovoltaics in tandem with holographic materials has led to a host of solar concentrating device designs that take advantage of the unique properties of diffractive optics. Compared to refractive optics, holographic devices are more lightweight and compact. This makes holographic devices …

Structured Dialogue State Management For Task-Oriented Dialogue Systems, Anh Duong Trinh

Doctoral

Human-machine conversational agents have developed at a rapid pace in recent years, bolstered through the application of advanced technologies such as deep learning. Today, dialogue systems are useful in assisting users in various activities, especially task-oriented dialogue systems in specific dialogue domains. However, they continue to be limited in many ways. Arguably the biggest challenge lies in the complexity of natural language and interpersonal communication, and the lack of human context and knowledge available to these systems. This leads to the question of whether dialogue systems, and in particular task-oriented dialogue systems, can be enhanced to leverage various language properties. …

Towards The Development Of A Balanced Legislative Framework For Consumer Data Protection In Electronic Commerce: The Case Of The Sultanate Of Oman, Talib Al Kharusi

Doctoral

This research aims to investigate whether the law as it currently stands in Oman provides adequate legal protection for personal data, to determine the current obstacles facing the electronic commerce sector, and to identify ways of overcoming such challenges. The empirical focus of this study will be electronic commerce transactions between companies and consumers. In this regard, the research will explore the perceptions of the main stakeholders towards privacy regulation and what implications these have for the growth of electronic commerce in Oman. The privacy that this research aims to explore is a complex issue since it concerns human feelings …

Comparing And Extending The Use Of Defeasible Argumentation With Quantitative Data In Real-World Contexts, Lucas Rizzo, Luca Longo

Articles

Dealing with uncertain, contradicting, and ambiguous information is still a central issue in Artificial Intelligence (AI). As a result, many formalisms have been proposed or adapted so as to consider non-monotonicity. A non-monotonic formalism is one that allows the retraction of previous conclusions or claims, from premises, in light of new evidence, offering some desirable flexibility when dealing with uncertainty. Among possible options, knowledge-base, non-monotonic reasoning approaches have seen their use being increased in practice. Nonetheless, only a limited number of works and researchers have performed any sort of comparison among them. This research article focuses on evaluating the inferential …

Comparing Poor And Favorable Outcome Prediction With Machine Learning After Mechanical Thrombectomy In Acute Ischemic Stroke, Matthias A. Mutke, Vince I. Madai, Adam Hilbert, Esra Zihni, Arne Potreck, Charlotte S. Weyland, Markus A. Mohlenbruch, Sabine Heiland, Peter A. Ringleb, Simon Nagel, Martin Beendszus, Dietmar Frey

Articles

Outcome prediction after mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and large vessel occlusion (LVO) is commonly performed by focusing on favorable outcome (modified Rankin Scale, mRS 0–2) after 3 months but poor outcome representing severe disability and mortality (mRS 5 and 6) might be of equal importance for clinical decision-making.

Corrigendum: Human Mental Workload: A Survey And A Novel Inclusive Definition, Luca Longo, Christopher D. Wickens, Gabriella Hancock, P. A. Hancock

Articles

In the published article, the name of Gabriella Hancock was incorrectly written as “Gabriela M. Hancock.” The correct name is “Gabriella Hancock.” In the published article, there was also an error in the author list as published. Gabriella Hancock was listed as the last author, but should have been listed as third author. P. A. Hancock was listed as third author but should be listed as the last author. The corrected author list appears below. Luca Longo1, Christopher D.Wickens, Gabriella Hancock and P. A. Hancock. The authors apologize for this error and state that this does not change the scientific …

Detection Of Grape Clusters In Images Using Convolutional Neural Network, Mohammad Osama Shahzad, Anas Bin Aqeel, Waqar Shahid Qureshi

Articles

Convolutional Neural Networks and Deep Learning have revolutionized every field since their inception. Agriculture has also been reaping the fruits of developments in mentioned fields. Technology is being revolutionized to increase yield, save water wastage, take care of diseased weeds, and also increase the profit of farmers. Grapes are among the highest profit-yielding and important fruit related to the juice industry. Pakistan being an agricultural country, can widely benefit by cultivating and improving grapes per hectare yield. The biggest challenge in harvesting grapes to date is to detect their cluster successfully; many approaches tend to answer this problem by harvest …

How Visual Stimuli Evoked P300 Is Transforming The Brain–Computer Interface Landscape: A Prisma Compliant Systematic Review, Jai Kalra, Prashasti Mittal, Nirmiti Mittal, Abhishek Arora, Utkarsh Tewari, Aviral Chharia, Rahul Upadhyay, Vinay Kumar, Luca Longo

Articles

Non-invasive Visual Stimuli evoked-EEGbased P300 BCIs have gained immense attention in recent years due to their ability to help patients with disability using BCI-controlled assistive devices and applications. In addition to the medical field, P300 BCI has applications in entertainment, robotics, and education. The current article systematically reviews 147 articles that were published between 2006-2021*. Articles that pass the pre-defined criteria are included in the study. Further, classification based on their primary focus, including article orientation, participants’ age groups, tasks given, databases, the EEG devices used in the studies, classification models, and application domain, is performed. The application-based classification considers …

Schizo-Net: A Novel Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning On Electroencephalogram-Based Brain Connectivity Indices, Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo

Articles

Schizophrenia (SCZ) is a serious mental condition that causes hallucinations, delusions, and disordered thinking. Traditionally, SCZ diagnosis involves the subject’s interview by a skilled psychiatrist. The process needs time and is bound to human errors and bias. Recently, brain connectivity indices have been used in a few pattern recognition methods to discriminate neuro-psychiatric patients from healthy subjects. The study presents Schizo-Net , a novel, highly accurate, and reliable SCZ diagnosis model based on a late multimodal fusion of estimated brain connectivity indices from EEG activity. First, the raw EEG activity is pre-processed exhaustively to remove unwanted artifacts. Next, six brain …

An Aggregation-Based Algebraic Multigrid Method With Deflation Techniques And Modified Generic Factored Approximate Sparse Inverses, Anastasia Natsiou, George A. Gravvanis, Christos K. Filelis-Papadopoulos, Konstantinos M. Giannoutakis

Articles

In this paper, we examine deflation-based algebraic multigrid methods for solving large systems of linear equations. Aggregation of the unknown terms is applied for coarsening, while deflation techniques are proposed for improving the rate of convergence. More specifically, the V-cycle strategy is adopted, in which, at each iteration, the solution is computed by initially decomposing it utilizing two complementary subspaces. The approximate solution is formed by combining the solution obtained using multigrids and deflation. In order to improve performance and convergence behavior, the proposed scheme was coupled with the Modified Generic Factored Approximate Sparse Inverse preconditioner. Furthermore, a parallel version …

Nesnet: A Deep Network For Estimating Near-Surface Pollutant Concentrations, Prasanjit Dey, Bibhash Pran Das, Yee Hui Lee, Soumyabrata Dev

Articles

Atmospheric pollution has become a serious threat in recent years. The advancements and expansion of industrial activity and civilization have been the major catalysts. With serious consequences like climate change and global warming, the onset of which is already being observed, keeping a check on atmospheric pollutant levels is now more important than ever. Trace gases play a major role in atmospheric chemistry. Many of these are also regarded as major atmospheric pollutants. The concentration of gases, such as (SO2), (O3), (NO2), etc., are indicators of air quality. Therefore, in this study, we primarily concern ourselves with concentrations of NO2, …

Do Games Reduce Math Anxiety? A Meta-Analysis, Pierpaolo Dondio, Viacheslav Filonenko, Mariana Rocha

Articles

In this paper, we meta-analyse the empirical evidence about the effectiveness of game-based interventions to reduce students' level of math anxiety. After performing a search for randomised controlled studies relevant to game-based intervention for math anxiety, 16 experimental studies with a total of 686 participants described in 11 peer-review articles met the selection criteria.A random-effects meta-analysis indicated a small and non-significant reduction of math anxiety (mean effect size ES=-0.32, CI=[-0.64,0.01]). The results were moderated by several factors: non-digital games were more effective, while digital games had a negligible mean effect size of $ES=-0.13$, $CI=[-0.33,0.08]$. The effect size was moderated also …

Rate Of Change Of Direct-Axis Current Component Protection Scheme For Inverter-Based Islanded Microgrids, Abdolhamid Farshadi, Behzad Keyvani Eydi, Hamed Nafisi, Hossein Askarian-Abyaneh, Arash Beiranvand

Articles

Rapid growth in the utilization of the inverter-interfaced distributed energy resources (IIDERs) in microgrids has brought new challenges in the network protection area. Microgrid protection specifically becomes a concern during operation in the islanded mode. There is a considerable reduction in fault current levels in this mode compared to when the microgrid is connected to the grid, which makes conventional algorithms operate with significant delay or, in many cases, not even pick up the fault. This paper proposes a protection algorithm based on the rate of change of direct-axis current component ( id ) to protect inverter-based microgrids (IBMGs). The …

Decision Making For Process Control Management In Control Rooms: A Survey Methodology And Initial Findings, Chidera Winifred Amazu, Ammar N. Abbas, Micaela Demichela, Davide Fissore

Articles

Control rooms and their operators are active elements in complex socio-technical systems such as process plants. Control room operators monitor process operations, respond to alarms, and manage process deviations until emergencies. The increase in automation of plants and equipment makes the operators less involved in manual process control or other physical roles while more exposed to cognitive load generated, for example, by increasing the number of alarms or potential system failures in abnormal situations. A shift in process control design and management techniques to holistically capture risks due to evolving process or monitoring capabilities and the related influencing factors is …

Opportunities Of Iot In Fog Computing For High Fault Tolerance And Sustainable Energy Optimization, A. Reyana, Sandeep Kautish, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

Today, the importance of enhanced quality of service and energy optimization has promoted research into sensor applications such as pervasive health monitoring, distributed computing, etc. In general, the resulting sensor data are stored on the cloud server for future processing. For this purpose, recently, the use of fog computing from a real-world perspective has emerged, utilizing end-user nodes and neighboring edge devices to perform computation and communication. This paper aims to develop a quality-of-service-based energy optimization (QoS-EO) scheme for the wireless sensor environments deployed in fog computing. The fog nodes deployed in specific geographical areas cover the sensor activity performed …

A Multidimensionality Reduction Approach To Rainfall Prediction, Menatallah Abdel Azeem, Prasanjit Dey, Soumyabrata Dev

Articles

The rainfall has an impact on various fields and industries, including transportation, construction, tourism, health, and wildlife preservation. Accurate rainfall prediction is essential for mitigating the negative impact of rainfall on these sectors. However, previous studies on rainfall prediction have been mainly based on datasets from North America, Europe, Australia, and Central Asia, covering different periods. This study proposes using weather datasets covering the past 5 to 10 years to capture recent patterns in weather data. Additionally, the curse of dimensionality can impact model performance and lead to overfitting. Therefore, this study proposes utilizing dimensionality reduction techniques to ensure that …

Assessing The Impact Of Contact Tracing With An Agent-Based Model For Simulating The Spread Of Covid-19: The Irish Experience, Elizabeth Hunter, Sudipta Saha, Jwenish Kumawat, Ciara Carroll, John Kelleher, Claire Buckley, Conor Mcaloon, Patricia Kearney, Michelle Gilbert, Greg Martin

Articles

Contact tracing is an important tool in managing infectious disease outbreaks and Ireland used a comprehensive contact tracing program to slow the spread of COVID-19. Although the benefits of contact tracing seem obvious, it is difficult to estimate the actual impact contact tracing has on an outbreak because it is hard to separate the effects of contact tracing from other behavioural changes or interventions. To understand the impact contact tracing had in Ireland, we used an agent-based model that is designed to simulate the spread of COVID-19 through Ireland. The model uses real contact tracing data from the first year …

Interpreting Disentangled Representations Of Person-Specific Convolutional Variational Autoencoders Of Spatially Preserving Eeg Topographic Maps Via Clustering And Visual Plausibility, Taufique Ahmed, Luca Longo

Articles

Dimensionality reduction and producing simple representations of electroencephalography (EEG) signals are challenging problems. Variational autoencoders (VAEs) have been employed for EEG data creation, augmentation, and automatic feature extraction. In most of the studies, VAE latent space interpretation is used to detect only the out-of-order distribution latent variable for anomaly detection. However, the interpretation and visualisation of all latent space components disclose information about how the model arrives at its conclusion. The main contribution of this study is interpreting the disentangled representation of VAE by activating only one latent component at a time, whereas the values for the remaining components are …

The Potential And Limitations Of Conversational Agents For Chronic Conditions And Well-Being, Ekaterina Uetova, Lucy Hederman, Robert J. Ross, Dympna O'Sullivan

Articles

Conversational agents are becoming more common in the health and wellness domains in part due to assumptions regarding potential improvements in individuals’ outcomes. This paper presents initial findings from a review of conversational agent use in healthcare for chronic conditions and well-being. A search of the literature was performed on electronic databases PubMed, ACM Digital Library, Scopus and IEEE Xplore. Studies were included if they were focused on chronic disorder management, disease prevention or lifestyle change and if systems were tested on target user groups. This paper investigates the health domains, the user profiles and reasons why conversational agents may …

Developing Persuasive Systems For Marketing: The Interplay Of Persuasion Techniques, Customer Traits And Persuasive Message Design, Annye Braca, Pierpaolo Dondio

Articles

This paper presents a comprehensive review of persuasion techniques and their applications in the context of designing persuasive communication systems for marketing purposes. The study provides a condensed taxonomy of techniques and offers examples to guide the development of effective persuasive messages. Furthermore, the paper explores how attitudes, personality traits, and emotions can be leveraged as input data in predictive models, including machine learning approaches. The study's findings offer valuable insights for the design and implementation of persuasive communication systems across diverse contexts, including marketing and advertising, public health campaigns, and political messaging. This paper has the potential to serve …

Supporting Clinical Decision Making In The Emergency Department For Paediatric Patients Using Machine Learning: A Scoping Review Protocol, Fiona Leonard, Dympna O. Sullivan, John Gilligan, Nicola O. Shea, Michael J. Barrett

Articles

Introduction Machine learning as a clinical decision support system tool has the potential to assist clinicians who must make complex and accurate medical decisions in fast paced environments such as the emergency department. This paper presents a protocol for a scoping review, with the objective of summarising the existing research on machine learning clinical decision support system tools in the emergency department, focusing on models that can be used for paediatric patients, where a knowledge gap exists. Materials and methods The methodology used will follow the scoping study framework of Arksey and O'Malley, along with other guidelines. Machine learning clinical …

Cognitive Engagement In Learning And Its Relationship To Cognitive Test Anxiety In Online Learning Courses During Coronavirus Pandemic Among University Students, Nafez Bukaiei

Journal of Educational and Psychological Studies

Abstract: The study aimed to reveal the relationship between cognitive engagement in learning and cognitive test anxiety in online learning courses among students of Faculty of Educational Sciences and Arts / UNRWA in Jordan. It also aimed to identify the level of cognitive engagement in learning and the level of cognitive test anxiety based on the variables of gender, faculty, and school year level. To achieve the study objectives, the researcher used two scales, the first measure was cognitive engagement in learning and the second measure was cognitive test anxiety. The study sample consisted of (n=262) male and female students. …