Finbarr Murphy

University of Limerick | UL · Department of Accounting and Finance

Workers involved in producing nanomaterials or using nanomaterials in manufacturing plants are likely to have earlier and higher exposure to manufactured/engineered nanomaterials (ENM) than the general population. This is because both the volume handled and the probability of the effluence of 'free' nanoparticles from the handled volume are much hi...

Without insurance the long-term sustainability of nanotechnology is questionable, but insurance companies are encumbered by their institutional memory of losses from the asbestos crisis and the absence of suitable actuarial models to measure the potential risks of nanotechnology. Here we propose a framework that supports the transfer of nanomateria...

Cybersecurity requires an effective risk transfer regime and a well‐functioning insurance market to improve stakeholder resilience. However, rapid cyber threat adaptation, limited data availability, and inadequate risk understanding pose significant challenges for the insurance industry and its customers. This research uses a mixed methods approach...

Generalized Linear Models (GLMs) and XGBoost are widely used in insurance risk pricing and claims prediction, with GLMs dominant in the insurance industry. The increasing prevalence of connected car data usage in insurance requires highly accurate and interpretable models. Deep learning (DL) models have outperformed traditional Machine Learning (ML...

Usage-based insurance has allowed insurers to dynamically tailor insurance premiums by understanding when and how safe policyholders drive. However, telematics information can also be used to understand the driving contexts experienced by the driver within each trip (e.g., road types, weather, traffic). Since different combinations of these conditi...

Reactive oxygen species (ROS) are compounds that readily transform into free radicals. Excessive exposure to ROS depletes antioxidant enzymes that protect cells, leading to oxidative stress and cellular damage. Nanomaterials (NMs) exhibit free radical scavenging efficiency representing a potential solution for oxidative stress-induced disorders. Th...

Advanced driver assistance systems (ADAS) present promising benefits in mitigating road collisions. However, these benefits are limited when risky drivers continue engaging in distraction events. While there is evidence that real-time warnings help improve driving behaviour, the sustained benefits of warning-based ADAS on reducing driving distracti...

Advanced Driver Assistance Systems (ADAS) have introduced several benefits in the vehicular industry, and their proliferation presents potential opportunities to decrease road accidents. The reasons are mainly attributed to the enhanced perception of the driving environment and reduced human errors. However, as environmental and infrastructural con...

In this paper, we uncover the essential features of websites that allow intelligent models to distinguish between phishing and legitimate sites. Phishing websites are those that are made with a similar user interface and a near similar address to trustworthy websites in order to persuade users to input their private data for potential future misuse...

The novel chemical strategy for sustainability calls for a Sustainable and Safe-by-Design (SSbD) holistic approach to achieve protection of public health and the environment, industrial relevance, societal empowerment, and regulatory preparedness. Based on it, the ASINA project expands a data-driven Management Methodology (ASINA-SMM) capturing qual...

The increasing accessibility of mobility datasets has enabled research in green mobility, road safety, vehicular automation, and transportation planning and optimization. Many stakeholders have leveraged vehicular datasets to study conventional driving characteristics and self-driving tasks. Notably, many of these datasets have been made publicly a...

In light of the potential long-term societal and economic benefits of novel nano-enabled products, there is an evident need for research and development to focus on closing the gap in nano-materials (NMs) safety. Concurrent reflection on the impact of decision-making tools, which may lack the capability to assist sophisticated judgements around the...

On the path to high-level vehicle automation, the degree of surveillance both inside and outside the car increases significantly. Consequently, ethical considerations are becoming central to questions around surveillance regimes and data privacy implicit in level 3 and 4 vehicle automation. In this paper, we focus on outputs from the EU Horizon 202...

In this paper, we demonstrate the realization process of a pragmatic approach on developing a template for capturing field monitoring data in nanomanufacturing processes. The template serves the fundamental principles which make data scientifically Findable, Accessible, Interoperable and Reusable (FAIR principles), as well as encouraging individual...

The emergence and rapid spread of multidrug-resistant bacteria strains are a public health concern. This emergence is caused by the overuse and misuse of antibiotics leading to the evolution of antibiotic-resistant strains. Nanoparticles (NPs) are objects with all three external dimensions in the nanoscale that varies from 1 to 100 nm. Research on...

We are facing an increase in the emergence of distracting activities while driving. This is especially the case for young people who, more than other age groups, employ their cars as a place of personal fulfilment. This study proposes an interdisciplinary safe-by-design (SbD) heuristic to address this emerging risk. It harnesses a German version of...

Background From February 2020, both urban and rural Ireland witnessed the rapid proliferation of the COVID-19 disease throughout its counties. During this period, the national COVID-19 responses included stay-at-home directives issued by the state, subject to varying levels of enforcement. Methods In this paper, we present a new method to assess a...

In this paper we describe the pragmatic approach of initiating, designing and implementing the Data Management Plan (DMP) and the data FAIRification process in the multidisciplinary Horizon 2020 nanotechnology project, Anticipating Safety Issues at the Design Stage of NAno Product Development (ASINA). We briefly describe the general DMP requirement...

The advent of automated vehicles is already taking place and will significantly disrupt the motor insurance industry. The shift from the human driver to the system as the driver cannot be reflected in the current insurance risk assessment. This call for an amendment of the insurance underwriting was discussed with German experts from both the prima...

A telematics device is a vehicle instrument that comes preinstalled by the vehicle manufacturer or can be added later. The device records information about driving behavior, including speed, acceleration, and turning force. When connected to vehicle computers, the device can also provide additional information regarding the mechanical usage and con...

Cyber-attacks pose a growing threat to global commerce that is increasingly reliant on digital technology to conduct business. Traditional risk assessment and underwriting practices face serious shortcomings when encountered with cyber threats. Conventional assessment frameworks rate risk based on historical frequency and severity of losses incurre...

The introduction of connected and autonomous vehicles (CAVs) to the road transport ecosystem will change the manner of collisions. CAVs are expected to optimize the safety of road users and the wider environment, while alleviating traffic congestion and maximizing occupant comfort. The net result is a reduction in the frequency of motor vehicle col...

Road traffic collisions are the leading cause of death for those between the ages of 15–29, according to the World Health Organisation. This study investigates one of the primary reasons for the high fatality rate amongst Young Novice Drivers (YNDs) – their use of smartphones while driving. We gathered responses from a representative sample of YNDs...

Our social relations are changing, we are now not just talking to each other, but we are now also talking to artificial intelligence (AI) assistants. We claim AI assistants present a new form of digital connectivity risk and a key aspect of this risk phenomenon relates to user risk awareness (or lack of) regarding AI assistant functionality. AI ass...

In Germany, every year 66,000 road crashes lead to death or injury of young novice drivers. This makes them twice as likely to be involved in, or cause, vehicle crashes compared to their older and more experienced counterparts. This study aims to address this societal issue by developing a better understanding of the German young driver problem. Fo...

Autonomous vehicles (AV) have advanced considerably over the past decade and their potential to reduce road accidents is without equal. That said, the evolution towards fully automated driving will be accompanied by new and unfamiliar risks. The deployment of AVs hinges on the premise that they are considerably safer than human drivers. However, th...

The practice of non-testing approaches in nanoparticles hazard assessment is necessary to identify and classify potential risks in a cost effective and timely manner. Machine learning techniques have been applied in the field of nanotoxicology with encouraging results. A neurotoxicity classification model for diverse nanoparticles is presented in t...

Nanotechnologies have reached maturity and market penetration that require nano‐specific changes in legislation and harmonization among legislation domains, such as the amendments to REACH for nanomaterials (NMs) which came into force in 2020. Thus, an assessment of the components and regulatory boundaries of NMs risk governance is timely, alongsid...

This study investigates the impact that delta-V, the relative change in vehicle velocity pre- and post-crash, has on the severity of motor vehicle collisions (MVCs). We study injury severity using two metrics for each occupant – the number of injuries suffered, and the probability of suffering a serious or worse (MAIS 3+) injury. We use a cross-sec...

Health care-associated infections (HAIs) affect millions of patients annually with up to 80,000 affected in Europe on any given day. This represents a significant societal and economic burden. Staff training, hand hygiene, patient identification and isolation and controlled antibiotic use are some of the standard ways to reduce HAI incidence but th...

Autonomous vehicles (AVs) are expected to considerably improve road safety. That said, accident risk will continue to inflict societal costs. The ability to manage and measure these risks is fundamental to ensure societal acceptance and public adoption of AVs. In particular, the ability to quantitatively compare the safety of AVs relative to human...

Motor Vehicle Collisions (MVCs) accounted for an economic cost of $242 billion in the United States in 2010. A significant portion (42%) was associated with factors considered for compensation estimates – medical costs, lost earnings and reduced household productivity. This study proposes a methodology that accounts for these costs by using expecte...

The exercise of non-testing approaches in nanoparticles (NPs) hazard assessment is necessary for the risk assessment, considering cost and time efficiency, to identify, assess, and classify potential risks. One strategy for investigating the toxicological properties of a variety of NPs is by means of computational tools that decode how nano-specifi...

Machine Learning (ML) techniques have been applied in the field of nanotoxicology with very encouraging results. Adverse effects of nanoforms are affected by multiple features described by theoretical descriptors, nano-specific measured properties, and experimental conditions. ML has been proven very helpful in this field in order to gain an insigh...

Road traffic accidents are largely driven by human error; therefore, the development of connected automated vehicles (CAV) is expected to significantly reduce accident risk. However, these changes are by no means proven and linear as different levels of automation show risk-related idiosyncrasies. A lack of empirical data aggravates the transparent...

In recent times the monitoring, examination, and potential reduction of risky driving behaviour by means of smartphone-based driver monitoring has been widely debated. This approach uses a combination of smartphone platform and big data sources to identify and interrogate risky driving behaviour in order to provide accurate feedback and promote saf...

This article aims to introduce a degree of technological and ethical realism to the framing of autonomous vehicle perception and decisionality. The objective is to move the socioethical dialog surrounding autonomous vehicle decisionality from the dominance of “trolley framings” to more pressing ethical issues. The article argues that more realistic...

Abstract The progressing interconnection and automation of automobile vehicles has profound implications for society and business operations. Existing business models and revenue streams in the automotive and transportation sector will be affected by this developing technology and a potential shift of societal mobility usage patterns. These disrupt...

Inroads have been made in our understanding of the risks posed to human health and the environment by nanoparticles (NPs) but this area requires continuous research and monitoring. Machine learning techniques have been applied to nanotoxicology with very encouraging results. This study deals with bridging physicochemical properties of NPs, experime...

Ctegories of ML classifiers (rules, trees, lazy, functions and bayes) were compared using datasets from the Safe and Sustainable Nanotechnology (S2NANO) database to investigate their performance in predicting NPs in vitro toxicity. Physicochemical properties, toxicological and quantum-mechanical attributes and in vitro experimental conditions were...

With the advent of autonomous vehicles society will need to confront a new set of risks which, for the first time, includes the ability of socially embedded forms of artificial intelligence to make complex risk mitigation decisions: decisions that will ultimately engender tangible life and death consequences. Since AI decisionality is inherently di...

The difficulty of beating the random walk in forecasting spot foreign exchange rates is well documented. In this paper, we propose a functional principal component-based scalar response model which we benchmark versus leading VECM frameworks. Our approach leads to near systematic outperformance in terms of a comparison of performance measures, and...

The provision of an adequate liability regime for ADAS technologies is an essential prerequisite for its roll out over the coming decade. Facing to the challenge of future highly automated vehicles, this paper proposed a Human-Machine Transition (HMT) approach as a common conceptual framework for considering Human Machine Interaction (HMI), liabili...

Complex Advanced Driving Assistance Systems (ADAS) and Autonomous Vehicle (AV) technology are increasing the number of vehicle recalls. At the same time, financial risks resulting from extensive product recall events can severely affect vehicle manufacturers and their suppliers, exposing the automotive supply chain to business continuity, legal and...

The question of the capacity of artificial intelligence to make moral decisions has been a key focus of investigation in robotics for decades. This question has now become pertinent to automated vehicle technologies, as a question of understanding the capacity of artificial driving intelligence to respond to unavoidable road traffic accidents. Arti...

Without nanosafety guidelines, the long-term sustainability of carbon nanotubes (CNTs) for water purifications is questionable. Current risk measurements of CNTs are overshadowed by uncertainties. New risks associated with CNTs are evolving through different waste water purification routes, and there are knowledge gaps in the risk assessment of CNT...

The proliferation of technologies embedded in connected and autonomous vehicles (CAVs) increases the potential of cyber-attacks. The communication systems between vehicles and infrastructure present remote attack access for malicious hackers to exploit system vulnerabilities. Increased connectivity combined with autonomous driving functions pose a...

The transition to semiautonomous driving is set to considerably reduce road accident rates as human error is progressively removed from the driving task. Concurrently, autonomous capabilities will transform the transportation risk landscape and significantly disrupt the insurance industry. Semiautonomous vehicle (SAV) risks will begin to alternate...

Rough draft.

In general, a functioning liability and insurance framework should ensure an adequate level of third party claimant protection and a reasonable and adequate final allocation of liability costs for the involved parties. This research examines whether the liability and insurance framework resulting from the amendment to German Road Traffic Act meets...

Societies worldwide are investing considerable resources into the safe development and use of nanomaterials. Although each of these protective efforts is crucial for governing the risks of nanomaterials, they are insufficient in isolation. What is missing is a more integrative governance approach that goes beyond legislation. Development of this ap...

Hazard identification is the key step in risk assessment and management of manufactured nanomaterials (NM). However, the rapid commercialisation of nano-enabled products continues to out-pace the development of a prudent risk management mechanism that is widely accepted by the scientific community and enforced by regulators. However, a growing body...

An extensive number of research studies have attempted to capture the factors that influence the severity of vehicle impacts. The high number of risks facing all traffic participants has led to a gradual increase in sophisticated data collection schemes linking crash characteristics to subsequent severity measures. This study serves as a departure...

Mental modelling analysis can be a valuable tool in understanding and bridging cognitive values in multi-stakeholders’ communities. It is especially true in situation of emerging risks where significant uncertainty and competing objectives could result in significant difference in stakeholder perspective on the use of new materials and technologies...

All developed economies mandate at least third party auto insurance resulting in a vast global liability industry. The evolution towards semi-autonomous and eventually driverless vehicles will progressively remove the leading cause of vehicle accidents, human error, and significantly lower vehicle accident rates. However, this transition will force...

The absence of nanotechnology-specific insurance policies could be detrimental to the development of the nanotechnology industry. Better communication between insurers and scientists is an essential step to provide a regulatory framework protecting both producers and consumers.

This paper examines the potential impact of the European Union’s Environmental Liability Directive (ELD) ¹ on the nanotechnology (NT) sector. In terms of risk governance the ELD represents a new paradigm, affording the environment an enhanced status both in legal and indeed ontological terms. However, the nature of the NT industry itself is such as...

In this study a Bayesian Network (BN) was developed for the prediction of the hazard potential and biological effects with the focus on metal- and metal-oxide nanomaterials to support human health risk assessment. The developed BN captures the (inter) relationships between the exposure route, the nanomaterials physicochemical properties, and the ul...

We utilise novel functional time series (FTS) techniques to characterise and forecast implied volatility in foreign exchange markets. In particular, we examine the daily implied volatility curves of FX options, namely; EUR-USD, EUR-GBP, and EUR-JPY. The FTS model is shown to produce both realistic and plausible implied volatility shapes that closel...