Physical Sciences and Mathematics Commons^™

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 …

Locating Identities In Time: An Examination Of The Impact Of Temporality On Presentations Of The Self Through Location-Based Social Networks, Konstantinos Papangelis, Ioanna Lykourentzou, Vassilis-Javed Khan, Alan Chamberlain, Ting Cao, Micahel Saker, Nicolas Lalone

Articles

Studies of identity and location-based social networks (LBSN) have tended to focus on the performative aspects associated with marking one’s location. Yet, these studies often present this practice as being an a priori aspect of locative media. What is missing from this research is a more granular understanding of how this process develops over time. Accordingly, we focus on the first six weeks of 42 users beginning to use an LBSN we designed and named GeoMoments. Through our analysis of our users' activities, we contribute to understanding identity and LBSN in two distinct ways. First, we show how LBSN users …

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 …

1d Conditional Generative Adversarial Network For Spectrum-To-Spectrum Translation Of Simulated Chemical Reflectance Signatures, Cara Murphy, John Kerekes

Articles

The classification of trace chemical residues through active spectroscopic sensing is challenging due to the lack of physics-based models that can accurately predict spectra. To overcome this challenge, we leveraged the field of domain adaptation to translate data from the simulated to the measured domain for training a classifier. We developed the first 1D conditional generative adversarial network (GAN) to perform spectrum-to-spectrum translation of reflectance signatures. We applied the 1D conditional GAN to a library of simulated spectra and quantified the improvement in classification accuracy on real data using the translated spectra for training the classifier. Using the GAN-translated library, …

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 …

Pivot Points In Bivariate Linear Regression, David L. Farnsworth, Carl V. Lutzer

Articles

There are little-noticed points in the plane, which are artifacts of linear regression. The points, which are called pivot points, are the intersections of sets of regression lines. We derive the coordinates of the pivot point and explain its sources. We show how a pivot point arises in a certain notable data set, which has been analyzed often for points of high leverage. We obtain the application of pivot points that shortens calculations when updating a set of bivariate observations by adding a new point.

A Geometric Approach To Conditioning And The Search For Minimum Variance Unbiased Estimators, David L. Farnsworth, James E. Marengo

Articles

Our purpose is twofold: to present a prototypical example of the conditioning technique to obtain the best estimator of a parameter and to show that this technique resides in the structure of an inner product space. The technique uses conditioning of an unbiased estimator on a sufficient statistic. This procedure is founded upon the conditional variance formula, which leads to an inner product space and a geometric interpretation. The example clearly illustrates the dependence on the sampling methodology. These advantages show the power and centrality of this process.

Temperature-Sensitive Holograms With Switchable Memory, Muhammad Irfan Dr, Suzanne Martin Dr, Izabela Naydenova Prof

Articles

Abstract

Herein, the dynamics and reversibility of temperature-induced changes in volume phase holographic gratings (VPHGs) recorded in the low-toxicity self-processing photopolymer poly(N-isopropyl acrylamide) (poly-NIPA) are reported on. Transmission and reflection gratings are exposed to temperatures ranging 8–60 °C to study the effect of temperature on their properties. First, the role of the photopolymer chemical composition is investigated by comparing layers containing NIPA with those containing acrylamide (AA) and measuring the normalized diffraction efficiency (DE) at 60 °C; higher thermal sensitivity is observed for poly-NIPA gratings (24% drop) versus low sensitivity for AA gratings (2% increase). The impact 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 …

Mining And Managing Big Data Refactoring For Design Improvement: Are We There Yet?, Eman Abdullah Alomar, Mohamed Wiem Mkaouer, Ali Ouni

Articles

Refactoring is a set of code changes applied to improve the internal structure of a program, without altering its external behavior. With the rise of continuous integration and the awareness of the necessity of managing technical debt, refactoring has become even more popular in recent software builds. Recent studies indicate that developers often perform refactorings. If we consider all refactorings performed across all projects, this consists of the refactoring knowledge that represents a rich source of information that can be useful for both developers and practitioners to better understand how refactoring is being applied in practice. However, mining, processing, and …

Refactoring Practices In The Context Of Modern Code Review: An Industrial Case Study At Xerox, Eman Abdullah Alomar, Hussein Alrubaye, Mohamed Wiem Mkaouer, Ali Ouni, Marouane Kessentini

Articles

Modern code review is a common and essential 2 practice employed in both industrial and open-source projects 3 to improve software quality, share knowledge, and ensure con4 formance with coding standards. During code review, developers 5 may inspect and discuss various changes including refactoring 6 activities before merging code changes in the code base. To date, 7 code review has been extensively studied to explore its general 8 challenges, best practices and outcomes, and socio-technical 9 aspects. However, little is known about how refactoring activities 10 are being reviewed, perceived, and practiced. 11 This study aims to reveal insights into …

Finding The Needle In A Haystack: On The Automatic Identification Of Accessibility User Reviews, Eman Abdullah Alomar, Wajdi Aljedaani, Murtaza Tamjeed, Mohamed Wiem Mkaouer, Yasime Elglaly

Articles

In recent years, mobile accessibility has become an important trend with the goal of allowing all users the possibility of using any app without many limitations. User reviews include insights that are useful for app evolution. However, with the increase in the amount of received reviews, manually analyzing them is tedious and time-consuming, especially when searching for accessibility reviews. The goal of this paper is to support the automated identification of accessibility in user reviews, to help technology professionals in prioritizing their handling, and thus, creating more inclusive apps. Particularly, we design a model that takes as input accessibility user …

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).

Physics-Guided Neural Network For Predicting Chemical Signatures, Cara Murphy, John Kerekes

Articles

Achieving high classification accuracy on trace chemical residues in active spectroscopic sensing is challenging due to the limited amount of training data available to the classifier. Such classifiers often rely on physics-based models for generating training data though these models are not always accurate when compared to measured data. To overcome this challenge, we developed a physics-guided neural network (PGNN) for predicting chemical reflectance for a set of parameterized inputs that is more accurate than the state-of-the-art physics-based signature model for chemical residues. After training the PGNN, we use it to generate a library of predicted spectra for training a …

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 …

The Potential Of Raman Spectroscopy In The Diagnosis Of Dysplastic And Malignant Oral Lesions, Ola Ibrahim, M. Toner, Steven Flint, Hugh Byrne, Fiona Lyng

Articles

Early diagnosis, treatment and/or surveillance of oral premalignant lesions are important in preventing progression to oral squamous cell carcinoma (OSCC). The current gold standard is through histopathological diagnosis, which is limited by inter and intra observer and sampling errors. The objective of this work was to use Raman spectroscopy to discriminate between benign, mild, moderate and severe dysplasia and OSCC in formalin fixed paraffin preserved (FFPP) tissues. The study included 72 different pathologies from which 17 were benign lesions, 20 mildly dysplastic, 20 moderately dysplastic, 10 severely dysplastic and 5 invasive OSCC. The glass substrate and paraffin wax background were …

Biomedical Applications Of Vibrational Spectroscopy: Oral Cancer Diagnostics, Hugh Byrne, Isha Behl, Genecy Calado, Ola Ibrahim, M. Toner, Sheila Galvin, Claire M. Healy, Steven Flint, Fiona Lyng

Articles

Vibrational spectroscopy, based on either infrared absorption or Raman scattering, has attracted increasing attention for biomedical applications. Proof of concept explorations for diagnosis of oral potentially malignant disorders and cancer are reviewed, and recent advances critically appraised. Specific examples of applications of Raman microspectroscopy for analysis of histological, cytological and saliva samples are presented for illustrative purposes, and the future prospects, ultimately for routine, chairside in vivo screening are discussed.

Collaborative Behavior, Performance And Engagement With Visual Analytics Tasks Using Mobile Devices, Lei Chen, Hai-Ning Liang, Feiyu Lu, Konstantinos Papangelis, Ka Lok Man, Yong Yue

Articles

Interactive visualizations are external tools that can support users’ exploratory activities. Collaboration can bring benefits to the exploration of visual representations or visu‐ alizations. This research investigates the use of co‐located collaborative visualizations in mobile devices, how users working with two different modes of interaction and view (Shared or Non‐Shared) and how being placed at various position arrangements (Corner‐to‐Corner, Face‐to‐Face, and Side‐by‐Side) affect their knowledge acquisition, engagement level, and learning efficiency. A user study is conducted with 60 partici‐ pants divided into 6 groups (2 modes×3 positions) using a tool that we developed to support the exploration of 3D visual …

The 3d Printing Of Dielectric Elastomer Films Assisted By Electrostatic Force, Yuhao Wang, Yanfen Zhou, Wenyue Li, Zhanxu Liu, Bangzi Zhou, Shipeng Wen, Liang Jiang, Shaojuan Che, Jianwei Ma, Tony Betts, Stephen Jerrams, Fenglei Zhou

Articles

ompared with traditional methods for preparing dielectric elastomer (DE) films, electrohydrodynamic (EHD) 3D printing displays many advantages, notably full automation, computer control and flexible design. It also confers high printing resolution, high preparation efficiency with minimal probability of nozzle clogging. In this article, EHD 3D printing was employed to fabricate silicone rubber (SR) based DE films. In order to increase their dielectric constant, high dielectric copper phthalocyanine (CuPc) particles were added into the SR ink. Optimal printing conditions were determined by analyzing the effects of printing voltage and ink properties on the formation of liquid cone and the printed line …

Multicomponent Fokas-Lenells Equations On Hermitian Symmetric Spaces, Vladimir Gerdjikov, Rossen Ivanov

Articles

Multi-component integrable generalizations of the Fokas-Lenells equation, associated with each irreducible Hermitian symmetric space are formulated. Description of the underlying structures associated to the integrability, such as the Lax representation and the bi-Hamiltonian formulation of the equations is provided. Two reductions are considered as well, one of which leads to a nonlocal integrable model. Examples with Hermitian symmetric spaces of all classical series of types A.III, BD.I, C.I and D.III are presented in details, as well as possibilities for further reductions in a general form.