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"Curran, Liam"
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An Exploration of Well-being in Former Covert and Undercover Police Officers
Little is known about the stressors of working in covert and undercover policing roles and the impact these can have on the health and psychological well-being of police officers. Extant literature focuses upon the social impact of undercover and covert policing in a democratic society, especially in relation to policing political groups. Presented here are the results of an exploratory study into the lives of former police officers who have engaged in various forms of covert/undercover policing. Utilising semi-structured interviews, in a five-participant case-study design, this research investigates the impact that covert and undercover policing has on the well-being of former officers who have undertaken this role, and how they utilised coping strategies. Data were thematically analysed using Braun and Clarke’s framework (Braun and Clarke
2006
). Findings were consistent in that fear of violence was a large factor that impacted the well-being and personal relationships of undercover officers. The paper concludes by outlining pertinent suggestions for future research and considers the implications for covert policing.
Journal Article
Understanding Fetal Alcohol Spectrum Disorder
This is the essential guide to FASD - the most common non-genetic learning disability, which is caused by alcohol consumption during pregnancy. It explains how FASD affects individuals at different stages of their lives, how you can identify it, and gives advice on how to support children, young people and adults with FASD.
eBook
Artificial intelligence for modelling infectious disease epidemics
Infectious disease threats to individual and public health are numerous, varied and frequently unexpected. Artificial intelligence (AI) and related technologies, which are already supporting human decision making in economics, medicine and social science, have the potential to transform the scope and power of infectious disease epidemiology. Here we consider the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science. We first outline how recent advances in AI can accelerate breakthroughs in answering key epidemiological questions and we discuss specific AI methods that can be applied to routinely collected infectious disease surveillance data. Second, we elaborate on the social context of AI for infectious disease epidemiology, including issues such as explainability, safety, accountability and ethics. Finally, we summarize some limitations of AI applications in this field and provide recommendations for how infectious disease epidemiology can harness most effectively current and future developments in AI.
This Perspective considers the application to infectious disease modelling of AI systems that combine machine learning, computational statistics, information retrieval and data science.
Journal Article
Large-scale predictions on turbulent gas-solid flows
The interaction of solid particles with turbulence has for long been a topic of interest for predicting the behaviour of industrially relevant flows. The flow interacts with the solid particles, the particles in turn modify the turbulent flow field, and particles collide with one another. The multi-level of interactions between the two-phases challenges our physical comprehension of these dynamical systems, as well as the numerical modelling strategies. Large-scale predictions on two-phase flows encompass the numerical solving of the largest turbulent structures and the tracking of large numbers of individual particles. Large Eddy Simulation methods are widely used for their low computational cost and accuracy in resolving most of the turbulent scales. In one-way coupled simulations however, the smallest scales can be relevant when considering second order dispersions of solid particles. A subgrid scale model is presented which enforces a correlation of the subgrid scale velocity of neighbouring particles, hence ensuring particle-pair dispersion statistics. Depending on their size and inertia, particles tend to accumulate in preferential regions forming clusters. A new numerical investigation on the turbulence modulation due to these large scale clusters is presented. A novel method for computing a characteristic length scale of clusters is introduced. Two-way coupled Direct Numerical Simulations of homogeneous isotropic turbulence are performed for a large range of particle Stokes number and mass loadings. A correlation is found between one the turbulent modulation length scales and the characteristic length scale of clusters. The Lagrangian framework is appreciated for its accuracy in tracking particle trajectories. However, in case of four-way coupling approach, the deterministic detection of colliding particle pairs becomes computationally very expensive. A new correlated stochastic model for particle collisions in the Lagrangian framework is introduced. The model is first validated for a homogeneous isotropic turbulence case, and then in a vertical channel flow.
Dissertation
Observer Magazine: Life & Style: Wheels: INCREDIBLE JOURNEY: LIAM CURRAN ON RUBBISH AND REVOLUTION IN NICARAGUA
Six weeks earlier we waved two dustcarts off on a banana boat in Ostend, wondering if they'd survive the passage through the Panama Canal during the US invasion. Three of us met them at the Pacific coast port of Corinto, and my friend Marcus and I proudly drove them to their new home. We picked up loads of Nicaraguan hitchhikers including a significant number in the \"crusher\" (disconnected for the trip).
Newspaper Article
Letter: Inquiry needed into union elections
[Kevin Curran] defeated the unelected acting general secretary Paul Kenny by a clear 2:1 majority in an election overseen by the Electoral Reform Society. No evidence has been produced to date that Kevin has been party to any alleged ballot rigging.
Newspaper Article