Physical Sciences and Mathematics Commons^™

A Framework Of Web-Based Dark Patterns That Can Be Detected Manually Or Automatically, Ioannis Stavrakakis, Andrea Curley, Dympna O'Sullivan, Damian Gordon, Brendan Tierney

Articles

This research explores the design and development of a framework for the detection of Dark Patterns, which are a series of user interface tricks that manipulate users into actions that they do not intend to do, for example, share more data than they want to, or spend more money than they plan to. The interface does this using either deception or other psychological nudges. User Interface experts have categorized a number of these tricks that are commonly used and have called them Dark Patterns. They are typically varied in their form and what they do, and the goal of this …

A Nanoscale Shape-Discovery Framework Supporting Systematic Investigations Of Shape-Dependent Biological Effects And Immunomodulation, Wei Zhang, Hender Lopez, Luca Boselli, Paolo Bigini, André Perez-Potti, Zengchun Xie, Valentina Castagnola, Qi Cai, Camila P. Silveira, Joao M. De Araujo, Laura Talamini, Nicolò Panini, Giuseppe Ristagno, Martina B. Violatto, Stéphanie Devineau, Marco P. Monopoli, Mario Salmona, Valeria A. Giannone, Sandra Lara, Kenneth A. Dawson, Yan Yan

Articles

Since it is now possible to make, in a controlled fashion, an almost unlimited variety of nanostructure shapes, it is of increasing interest to understand the forms of biological control that nanoscale shape allows. However, a priori rational investigation of such a vast universe of shapes appears to present intractable fundamental and practical challenges. This has limited the useful systematic investigation of their biological interactions and the development of innovative nanoscale shape-dependent therapies. Here, we introduce a concept of biologically relevant inductive nanoscale shape discovery and evaluation that is ideally suited to, and will ultimately become, a vehicle for machine …

The Circle Of Life: The Mathematics Of Predator-Prey Dynamics, John Butler, Rebecca Brady

Articles

Some animals hunt other animals to feed themselves; these animals are called predators. Animals who are hunted and eaten are known as prey. What do you think would happen if a predator were introduced to an ecosystem where the prey previously lived without fear of being hunted? Would the new predator eat all the prey animals until they go extinct? Actually, the relationship between predator and prey is far more interesting than this. In this article, we show what the predator-prey relationship looks like over time and explain how scientists can make predictions about future population levels, all using basic …

Explaining Deep Learning Models For Tabular Data Using Layer-Wise Relevance Propagation, Ihsan Ullah, Andre Rios, Vaibhov Gala, Susan Mckeever

Articles

Trust and credibility in machine learning models are bolstered by the ability of a model to explain its decisions. While explainability of deep learning models is a well-known challenge, a further challenge is clarity of the explanation itself for relevant stakeholders of the model. Layer-wise Relevance Propagation (LRP), an established explainability technique developed for deep models in computer vision, provides intuitive human-readable heat maps of input images. We present the novel application of LRP with tabular datasets containing mixed data (categorical and numerical) using a deep neural network (1D-CNN), for Credit Card Fraud detection and Telecom Customer Churn prediction use …

Newgrange Skyscape In Stellarium, Frank Prendergast

Articles

Newgrange Skyscape in Stellarium is a new customised landscape planetarium model giving the user the unique ability to interrogate the dynamic sky above the Boyne Valley on any date of interest during the hours of daylight or darkness. Archaeological, astronomical and topographical points of interest are labelled in the model and visible even during the hours of darkness. These are summarily described in a short gazetteer appended at the end of the instruction document to encourage further exploration of the wonderful heritage found in the Boyne Valley and beyond.

Watch on Youtube: https://www.youtube.com/watch?app=desktop&v=aGPsVGBXkY4

Watch on Vimeo: https://vimeo.com/493351576

Notions Of Explainability And Evaluation Approaches For Explainable Artificial Intelligence, Giulia Vilone, Luca Longo

Articles

Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few years. This is due to the widespread application of machine learning, particularly deep learning, that has led to the development of highly accurate models that lack explainability and interpretability. A plethora of methods to tackle this problem have been proposed, developed and tested, coupled with several studies attempting to define the concept of explainability and its evaluation. This systematic review contributes to the body of knowledge by clustering all the scientific studies via a hierarchical system that classifies theories and notions related to the concept of explainability …

A Novel Parabolic Model Of Instructional Efficiency Grounded On Ideal Mental Workload And Performance, Luca Longo, Murali Rajendran

Articles

Instructional efficiency within education is a measurable concept and models have been proposed to assess it. The main assumption behind these models is that efficiency is the capacity to achieve established goals at the minimal expense of resources. This article challenges this assumption by contributing to the body of Knowledge with a novel model that is grounded on ideal mental workload and performance, namely the parabolic model of instructional efficiency. A comparative empirical investigation has been constructed to demonstrate the potential of this model for instructional design evaluation. Evidence demonstrated that this model achieved a good concurrent validity with the …

Provenance: An Intermediary-Free Solution For Digital Content Verification, Bilal Yousuf, M. Atif Qureshi, Brendan Spillane, Gary Munnelly, Oisin Carroll, Matthew Runswick, Kirsty Park, Eileen Culloty, Owen Conlan, Jane Suiter

Articles

The threat posed by misinformation and disinformation is one of the defining challenges of the 21st century. Provenance is designed to help combat this threat by warning users when the content they are looking at may be misinformation or disinformation. It is also designed to improve media literacy among its users and ultimately reduce susceptibility to the threat among vulnerable groups within society. The Provenance browser plugin checks the content that users see on the Internet and social media and provides warnings in their browser or social media feed. Unlike similar plugins, which require human experts to provide evaluations and …

Towards A Framework For Comparing Functionalities Of Multimorbidity Clinical Decision Support: A Literature-Based Feature Set And Benchmark Cases., Dympna O'Sullivan, William Van Woensel, Szymon Wilk, Samson Tu, Wojtek Michalowski, Samina Abidi, Marc Carrier, Ruth Edry, Irit Hochberg, Stephen Kingwell, Alexandra Kogan, Martin Michalowski, Hugh O'Sullivan, Mor Peleg

Articles

Multimorbidity, the coexistence of two or more health conditions, has become more prevalent as mortality rates in many countries have declined and their populations have aged. Multimorbidity presents significant difficulties for Clinical Decision Support Systems (CDSS), particularly in cases where recommendations from relevant clinical guidelines offer conflicting advice. A number of research groups are developing computer-interpretable guideline (CIG) modeling formalisms that integrate recommendations from multiple Clinical Practice Guidelines (CPGs) for knowledge-based multimorbidity decision support. In this paper we describe work towards the development of a framework for comparing the different approaches to multimorbidity CIG-based clinical decision support (MGCDS). We present …

A Quantitative Evaluation Of Global, Rule-Based Explanations Of Post-Hoc, Model Agnostic Methods, Giulia Vilone, Luca Longo

Articles

Understanding the inferences of data-driven, machine-learned models can be seen as a process that discloses the relationships between their input and output. These relationships consist and can be represented as a set of inference rules. However, the models usually do not explicit these rules to their end-users who, subsequently, perceive them as black-boxes and might not trust their predictions. Therefore, scholars have proposed several methods for extracting rules from data-driven machine-learned models to explain their logic. However, limited work exists on the evaluation and comparison of these methods. This study proposes a novel comparative approach to evaluate and compare the …

Synergistic Anticancer Response Of Curcumin And Piperine Loaded Lignin-G-P (Nipam-Co-Dmaema) Gold Nanogels Against Glioblastoma Multiforme, Xinyi Zhao, Bilal Javad, Daxing Cui, James Curtin, Furong Tian

Articles

Glioblastoma multiforme (GBM) is the most aggressive and commonly diag- 11 nosed brain cancer and presents a strong resistance to routine chemotherapeutic drugs. 12 The present study involves the synthesis of Lignin-g- p (NIPAM-co-DMAEMA) gold 13 nanogel, loaded with curcumin and piperine to treat GBM. The application has three 14 functions: (1) overcome the limitations of biodistribution, (2) enhance the toxicity of an- 15 ticancer drugs against GBM, (3) identify the uptake pathway. Atom transfer radical 16 polymerization was used to synthesize the Lignin-g-PNIPAM network, crosslinked with 17 the gold nanoparticles (GNPs) to self-assemble into nanogels. The size distribution and …

Cleanpage: Fast And Clean Document And Whiteboard Capture, Jane Courtney

Articles

The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory. Available scanning apps vary in their usability and do not always produce clean results, retaining surface imperfections from the page or whiteboard in their output images. CleanPage, a novel smartphone-based document and whiteboard scanning system, is presented. CleanPage requires one button-tap to capture, identify, crop, and …

Sediqa: Sound Emitting Document Image Quality Assessment In A Reading Aid For The Visually Impaired, Jane Courtney

Articles

For visually impaired people (VIPs), the ability to convert text to sound can mean a new level of independence or the simple joy of a good book. With significant advances in optical character recognition (OCR) in recent years, a number of reading aids are appearing on the market. These reading aids convert images captured by a camera to text which can then be read aloud. However, all of these reading aids suffer from a key issue—the user must be able to visually target the text and capture an image of sufficient quality for the OCR algorithm to function—no small task …

Profiling Mathematical Procedural And Problem-Solving Skills Of Undergraduate Students Following A New Mathematics Curriculum, Fiona Faulkner, Mark Prendergast, Cormac Breen, Michael Carr

Articles

In 2010 a mathematics curriculum was introduced in Irish second level schools entitled ‘Project Maths’ (PM). It aimed to refocus second level mathematics teaching and learning away from an over emphasis on procedural mathematics towards problem solving and real understanding [Department of Education and Skills (DES). (2010). Report of the Project Maths implementation support group. https://www.education.ie/en/Publications/Policy-Reports/Report-of-the-Project-Maths-Implementation-Group.pdf]. This paper aims to examine the performance of 1st year undergraduate students’ procedural and problem solving skills after the introduction of PM. A diagnostic test was developed to determine students’ skills in each area and findings demonstrated that students perform statistically significantly …

Immobilized-Enzyme Reactors Integrated Into Analytical Platforms: Recent Advances And Challenges, Bert Wouters Dr, Sinead Currivan, Noor Abdulhussain, T. Hankemeier, Peter J. Schoenmakers

Articles

Immobilized-enzyme reactors (IMERs) are flow-through devices containing enzymes that are physically confined or localized with retention of their catalytic activities. IMERs can be used repeatedly and continuously and have been applied for (bio)polymer degradation, proteomics, biomarker discovery, inhibitor screening, and detection. Online integration of IMERs with analytical instrumentation, such as high-performance liquid chromatography (HPLC) systems, reduces the time needed for multi-step workflows, reduces the need for sample handling, and enables automation. However, online integration can also be challenging, as reaching its full potential requires complex instrumental setups and experienced users. This review aims to provide an assessment of recent advances …

Classification Of Explainable Artificial Intelligence Methods Through Their Output Formats, Giulia Vilone, Luca Longo

Articles

Machine and deep learning have proven their utility to generate data-driven models with high accuracy and precision. However, their non-linear, complex structures are often difficult to interpret. Consequently, many scholars have developed a plethora of methods to explain their functioning and the logic of their inferences. This systematic review aimed to organise these methods into a hierarchical classification system that builds upon and extends existing taxonomies by adding a significant dimension—the output formats. The reviewed scientific papers were retrieved by conducting an initial search on Google Scholar with the keywords “explainable artificial intelligence”; “explainable machine learning”; and “interpretable machine learning”. …

A Health Elearning Ontology And Procedural Reasoning Approach For Developing Personalized Courses To Teach Patients About Their Medical Condition And Treatment, Martin Michalowski, Szymon Wilk, Wojtek Michalowski, Dympna O'Sullivan, Silvia Bonaccio, Enea Parimbelli, Marc Carrier, Grégoire Le Gal, Stephen Kingwell, Mor Peleg

Articles

We propose a methodological framework to support the development of personalized courses that improve patients’ understanding of their condition and prescribed treatment. Inspired by Intelligent Tutoring Systems (ITSs), the framework uses an eLearning ontology to express domain and learner models and to create a course. We combine the ontology with a procedural reasoning approach and precompiled plans to operationalize a design across disease conditions. The resulting courses generated by the framework are personalized across four patient axes—condition and treatment, comprehension level, learning style based on the VARK (Visual, Aural, Read/write, Kinesthetic) presentation model, and the level of understanding of specific …

Biochemical Impact Of Solar Radiation Exposure On Human Keratinocytes Monitored By Raman Spectroscopy; Effects Of Cell Culture Environment, Ulises Lopez Gonzalez, Alan Casey, Hugh Byrne

Articles

Understanding and amelioration of the effects of solar radiation exposure are critical in preventing the occurrence of skin cancer. Towards this end, many studies have been conducted in 2D cell culture models under simplified and unrealistic conditions. 3D culture models better capture the complexity of in vivo physiology, although the effects of the 3D extracellular matrix have not been well studied. Monitoring the instantaneous and resultant cellular responses to exposure, and the influence of the 3D environment, could provide an enhanced understanding of the fundamental processes of photocarcinogenesis. This work presents an analysis of the biochemical impacts of simulated solar …

Flying Free: A Research Overview Of Deep Learning In Drone Navigation Autonomy, Thomas Lee, Susan Mckeever, Jane Courtney

Articles

With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete autonomy. However, while much work in the area focuses on specific tasks in drone navigation, the contribution to the overall goal of autonomy is often not assessed, and a comprehensive overview is needed. In this work, a taxonomy of drone navigation autonomy is established by mapping the definitions of vehicular autonomy levels, as defined by the …

Adapting An Agent-Based Model Of Infectious Disease Spread In An Irish County To Covid-19, Elizabeth Hunter, John D. Kelleher

Articles

The dynamics that lead to the spread of an infectious disease through a population can be characterized as a complex system. One way to model such a system, in order to improve preparedness, and learn more about how an infectious disease, such as COVID-19, might spread through a population, is agent-based epidemiological modelling. When a pandemic is caused by an emerging disease, it takes time to develop a completely new model that captures the complexity of the system. In this paper, we discuss adapting an existing agent-based model for the spread of measles in Ireland to simulate the spread of …

Internet Of Medical Things (Iomt): Overview, Emerging Technologies, And Case Studies, Sahshanu Razdan, Sachin Sharma

Articles

No abstract provided.

Raman Spectroscopic Characterisation Of Non Stimulated And Stimulated Human Whole Saliva, Genecy Calado, Isha Behl, Hugh Byrne, Fiona Lyng

Articles

Human saliva is a unique biofluid which can reflect the physiopathological state of an individual. The wide spectrum of molecules present in saliva, compounded by the close association of salivary composition to serum metabolites, can provide valuable information for clinical diagnostic applications through highly sensitive vibrational spectroscopic techniques such as Raman spectroscopy. However, the nature of saliva, in terms of collection and patient-related characteristics, can be considered factors which may strongly affect the Raman spectral profile of salivary samples and disrupt the search for specific salivary biomarkers in the detection of diseases. The main objective of this study was to …

On The Socles Of Fully Inert Subgroups Of Abelian P-Groups, Andrey R. Chekhlov, Peter V. Danchev, Brendan Goldsmith

Articles

We define the so-called fully inert socle-regular and weakly fully inert socle-regular Abelian p-groups and study them with respect to certain of their numerous interesting properties. For instance, we prove that in the case of groups of length ω, these two group classes coincide, but that in the case of groups of length ω+1, they differ. Some structural and characterization results are also obtained. The work generalizes concepts which have been of interest recently in the theory of entropy in algebra and builds on recent investigations by Danchev and Goldsmith (Arch Math (3) 92:191–199, 2009; J Algebra 323:3020–3028, 2010).

On The Socles Of Characteristically Inert Subgroups Of Abelian P-Groups, Andrey R. Chekhlov, Peter V. Danchev, Brendan Goldsmith

Articles

We define the notion of a characteristically inert socle-regular Abelian p-group and explore such groups by focussing on their socles, thereby relating them to previously studied notions of socle-regularity. We show that large classes of p-groups, including all divisible, totally projective and torsion-complete p-groups, share this property when the prime p is odd. The present work generalizes notions of full inertia intensively studied recently by several authors and is a development of a recent work of the authors published in Mediterranean J. Math. (2021).

Virtual Network Function Embedding Under Nodal Outage Using Deep Q-Learning, Swarna Bindu Chetty, Hamed Ahmadi, Sachin Sharma, Avishek Nag

Articles

With the emergence of various types of applications such as delay-sensitive applications, future communication networks are expected to be increasingly complex and dynamic. Network Function Virtualization (NFV) provides the necessary support towards efficient management of such complex networks, by virtualizing network functions and placing them on shared commodity servers. However, one of the critical issues in NFV is the resource allocation for the highly complex services; moreover, this problem is classified as an NP-Hard problem. To solve this problem, our work investigates the potential of Deep Reinforcement Learning (DRL) as a swift yet accurate approach (as compared to integer linear …

Metrics For Performance Quantification Of Adaptive Mesh Refinement, Nicole Beisiegel, Cristóbal E. Castro, Jörn Behrens

Articles

Non-uniform, dynamically adaptive meshes are a useful tool for reducing computational complexities for geophysical simulations that exhibit strongly localised features such as is the case for tsunami, hurricane or typhoon prediction. Using the example of a shallow water solver, this study explores a set of metrics as a tool to distinguish the performance of numerical methods using adaptively refined versus uniform meshes independent of computational architecture or implementation. These metrics allow us to quantify how a numerical simulation benefits from the use of adaptive mesh refinement. The type of meshes we are focusing on are adaptive triangular meshes that are …

Using A Hybrid Agent-Based And Equation Based Model To Test School Closure Policies During A Measles Outbreak, Elizabeth Hunter, John D. Kelleher

Articles

Background

In order to be prepared for an infectious disease outbreak it is important to know what interventions will or will not have an impact on reducing the outbreak. While some interventions might have a greater effect in mitigating an outbreak, others might only have a minor effect but all interventions will have a cost in implementation. Estimating the effectiveness of an intervention can be done using computational modelling. In particular, comparing the results of model runs with an intervention in place to control runs where no interventions were used can help to determine what interventions will have the greatest …

The Prospect Of Microwave Heating: Towards A Faster And Deeper Crack Healing In Asphalt Pavement, Shi Xu, Xueyan Liu, Amir Tabakovic, Erik Schlangen

Articles

Microwave heating has been shown to be an effective method of heating asphalt concrete and in turn healing the damage. As such, microwave heating holds great potential in rapid (1–3 min) and effective damage healing, resulting in improvement in the service life, safety, and sustainability of asphalt pavement. This study focused on the microwave healing effect on porous asphalt concrete. Steel wool fibres were incorporated into porous asphalt to improve the microwave heating efficiency, and the optimum microwave heating time was determined. Afterwards, the microwave healing efficiency was evaluated using a semi–circular bending and healing programme. The results show that …

Diagnostics Of A Large Volume Pin-To-Plate Atmospheric Plasma Source For The Study Of Plasma Species Interactions With Cancer Cell Cultures, Laurence Scally, Chaitanya Sarangapani, Brijesh Tiwari, Renee Malone, Hugh Byrne, James Curtin, P.J. Cullen

Articles

A large gap pin-to-plate, atmospheric pressure plasma reactor is demonstrated as means of in vitro study of plasma species interactions with cell cultures. By employing optical emission and optical absorption spectroscopy, we report that the pin-to-pate plasma array had an optimal discharge frequency for cell death of 1000 Hz in ambient air for the target cancer cell line; human glioblastoma multiform (U-251MG). The detected plasma chemistry contained reactive oxygen and nitrogen species including OH, N₂, N₂⁺, and O₃. We show that, by varying the plasma discharge frequency, the plasma chemistry can be tailored …

Impact Of Dynamic Sub-Populations Within Grafted Chains On The Protein Binding And Colloidal Stability Of Pegylated Nanoparticles, Delyan Hristov, Hender Lopez, Yannick Ortin, Kate O'Sullivan, Kenneth A. Dawson, Dermot F. Brougham

Articles

Polyethylene glycol grafting has played a central role in preparing the surfaces of nano-probes for biological interaction, to extend blood circulation times and to modulate protein recognition and cellular uptake. However, the role of PEG graft dynamics and conformation in determining surface recognition processes is poorly understood primarily due to the absence of a microscopic picture of the surface presentation of the polymer. Here a detailed NMR analysis reveals three types of dynamic ethylene glycol units on PEG-grafted SiO2 nanoparticles (NPs) of the type commonly evaluated as long-circulating theranostic nano-probes; a narrow fraction with fast dynamics associated with the chain …