Towards a Mirror System for the Development of Socially-Mediated Skills

We present a system that attempts to model the functional role of mirror neurons, namely the activation of structures in response to both the observation of a demonstrated task, and its generation. Through social situatedness and a set of innate skills, perceptual and motor structures develop for recognition and reproduction of demonstrated actions. We believe this is an implementation towards a mirror system, and we test it on two platforms, one in simulation involving imitation of object interactions, the second on a physical robot learning from a human to follow walls

EvoTanks: co-evolutionary development of game-playing agents

This paper describes the EvoTanks research project, a continuing attempt to develop strong AI players for a primitive 'Combat' style video game using evolutionary computational methods with artificial neural networks. A small but challenging feat due to the necessity for agent's actions to rely heavily on opponent behaviour. Previous investigation has shown the agents are capable of developing high performance behaviours by evolving against scripted opponents; however these are local to the trained opponent. The focus of this paper shows results from the use of co-evolution on the same population. Results show agents no longer succumb to trappings of local maxima within the search space and are capable of converging on high fitness behaviours local to their population without the use of scripted opponents

Quality care, public perception and quick-fix service management: a Delphi study on stressors of hospital doctors in Ireland.

OBJECTIVES: To identify and rank the most significant workplace stressors to which consultants and trainees are exposed within the publicly funded health sector in Ireland. DESIGN: Following a preliminary semistructured telephone interview, a Delphi technique with 3 rounds of reiterative questionnaires was used to obtain consensus. Conducted in Spring 2014, doctors were purposively selected by their college faculty or specialty training body. SETTING: Consultants and higher specialist trainees who were engaged at a collegiate level with their faculty or professional training body. All were employed in the Irish publicly funded health sector by the Health Services Executive. PARTICIPANTS: 49 doctors: 30 consultants (13 male, 17 female) and 19 trainees (7 male, 12 female). Consultants and trainees were from a wide range of hospital specialties including anaesthetics, radiology and psychiatry. RESULTS: Consultants are most concerned with the quality of healthcare management and its impact on service. They are also concerned about the quality of care they provide. They feel undervalued within the negative sociocultural environment that they work. Trainees also feel undervalued with an uncertain future and they also perceive their sociocultural environment as negative. They echo concerns regarding the quality of care they provide. They struggle with the interface between career demands and personal life. CONCLUSIONS: This Delphi study sought to explore the working life of doctors in Irish hospitals at a time when resources are scarce. It identified both common and distinct concerns regarding sources of stress for 2 groups of doctors. Its identification of key stressors should guide managers and clinicians towards solutions for improving the quality of patient care and the health of care providers

Weighted risk assessment of critical source areas for soil phosphorus losses through surface runoff mechanisms

This work was supported by the NERC QUADRAT DTP [grant number 2280708].Peer reviewedPublisher PD

The challenges, uncertainties and opportunities of bioaerosol dispersion modelling from open composting facilities

Bioaerosols are ubiquitous organic particles that comprise viruses, bacteria and coarser fractions of organic matter. Known to adversely affect human health, the impact of bioaerosols on a population often manifests as outbreaks of illnesses such as Legionnaires Disease and Q fever, although the concentrations and environmental conditions in which these impacts occur are not well understood. Bioaerosol concentrations vary from source to source, but specific human activities such as water treatment, intensive agriculture and composting facilitate the generation of bioaerosol concentrations many times higher than natural background levels. Bioaerosols are not considered ‘traditional’ pollutants in the same way as PM10, PM2.5, and gases such as NO2, and consequently dispersion models do not include a bespoke method for their assessment. As identified in previous studies, priority areas for improving the robustness of these dispersion models include: 1) the development of bespoke monitoring studies designed to generate accurate modelling input data; 2) the publication of a robust emissions inventory; 3) a code of practice to provide guidelines for consistent bioaerosol modelling practices; and 4) a greater understanding of background bioaerosol emissions. The aim of this research project, funded by the Natural Environmental Research Council (NERC), is to address these key areas through a better understanding of the generation, concentration and potential dispersion of bioaerosols from intensive agricultural and biowaste facilities, using case studies developed at specific locations within the UK. The objective is to further refine existing bioaerosol monitoring and modelling guidelines to provide a more robust framework for regulating authorities and site operators. This contribution outlines the gaps that hinder robust dispersion modelling, and describes the on-site bioaerosol data collection methods used in the study, explaining how they might be used to close these gaps. Examples of bioaerosol dispersion modelled using ADMS 5 are presented and discussed

Towards improved bioaerosol model validation and verification

Bioaerosols, comprised of bacteria, fungi and viruses are ubiquitous in ambient air. Known to adversely affect human health, the impact of bioaerosols on a population often manifests as outbreaks of illnesses such as Legionnaires Disease and Q fever, although the concentrations and environmental conditions in which these impacts occur are not well understood. Bioaerosol concentrations vary from source to source, but specific industrialised human activities such as water treatment, intensive agriculture and open windrow composting facilitate the generation of bioaerosol concentrations many times higher than natural background levels. Bioaerosol sampling is currently undertaken according to the requirements of the Environment Agency’s regulatory framework, in which the collection of bioaerosols and not its long-term measurement is of most importance. As a consequence, sampling devices are often moved around site according to changing wind direction and sampling intervals are invariably short-term. The dispersion modelling of bioaerosols from composting facilities typically relies on proxy pollutant parameters. In addition, the use of short term emission data gathering strategies in which monitors are moved frequently with wind direction, do not provide a robust reliable and repeatable dataset by which to validate any modelling or to verify its performance. New sampling methods such as the Spectral Intensity Bioaerosol Sensor (SIBS) provide an opportunity to address several gaps in bioaerosol model validation and verification. In the context of model validation, this paper sets out the current weaknesses in bioaerosol monitoring from the perspective of robust modelling requirements

A Forward Model of Optic Flow for Detecting External Forces

Robot positioning is an important function of autonomous intelligent robots. However, the application of external forces to a robot can disrupt its normal operation and cause localisation errors. We present a novel approach for detecting external disturbances based on optic flow without the use of egomotion information. Even though this research moderately validates the efficacy of the model we argue that its application is plausible to a large number of robotic systems

Representing Trees with Constraints

Proceedings of the First International Conference on Computational Logic (CL2000)This paper presents a method for representing trees using constraint logic programming over finite domains. We describe a class of trees that is of particular interest to us and how we can represent the set of trees belonging to that class using constraints. The method enables the specification of a set of trees without having to generate all of the members of the set. This allows us to reason about sets of trees that would normally be too large to use. We present this research in the context of a system to generate expressive musical performances and, in particular, how this method can be used to represent musical structure

"Will I always be not social?": Re-Conceptualizing Sociality in the Context of a Minecraft Community for Autism

Traditional face-to-face social interactions can be challenging for individuals with autism, leading some to perceive and categorize them as less social than their typically-developing peers. Individuals with autism may even see themselves as less social relative to their peers. Online communities can provide an alternative venue for social expression, enabling different types of communication beyond face-to-face, oral interaction. Using ethnographic methods, we studied the communication ecology that has emerged around a Minecraft server for children with autism and their allies. Our analysis shows how members of this community search for, practice, and define sociality through a variety of communication channels. These findings suggest an expansion in how sociality has traditionally been conceptualized for individuals with autism