New challenges faced by carers during their child's hospital admission under segregation

Introduction
This paper presents the results of a qualitative study of CF family carers at the Belfast Paediatric CF Centre. The aim of this study was to describe the carer experience of their child’s admission to hospital under segregated care arrangements, and to highlight the meaning of segregation and cross infection from the carer perspective.

Method
Carers of children with CF who were admitted for two week IV antibiotic treatment during the study period were eligible to participate in this qualitative study. A consecutive series of eligible carers were approached in order of admission and within the time constraints of KR who was present two days each week. Recruitment of carers ended when no new themes emerged. Ten carers, 9 mothers and 1 couple, were interviewed about their experiences (mean age of child: 11.8 years; range: 1-17 years). Interpretative Phenomenological Analysis (IPA) was used to analyse and interpret the interview data.

Results and discussion
Balancing demands and dilemmas was the main contextual theme or experience of being a carer of a child with CF, and particularly so during admission to hospital. Many decisions were required every day that resulted in ‘double binds’ comprising uncertainty and stress. Three secondary themes captured the essence of carers’ experiences specifically related to segregation: managing risk and uncertainty; the burden of admission; and getting through each day. These themes will be described with examples illustrating the challenges faced by carers during their child’s hospitalisation, and the impact of segregation upon carers.

An Improvement of Subject Reacquisition by Reasoning and Revision

CCTV systems are broadly deployed in the present world. Despite this, the impact on anti-social and criminal behaviour has been minimal. Subject reacquisition is a fundamental task to ensure in-time reaction for intelligent surveillance. However, traditional reacquisition based on face recognition is not scalable, hence in this paper we use reasoning techniques to reduce the computational effort which deploys the time-of-flight information between interested zones such as airport security corridors. Also, to improve accuracy of reacquisition, we introduce the idea of revision as a method of post-processing.We demonstrate the significance and usefulness of our framework with an experiment which shows much less computational effort and better accuracy.

Blocking in children's causal learning depends on working memory and reasoning abilities.

A sample of 99 children completed a causal learning task that was an analogue of the food allergy paradigm used with adults. The cue competition effects of blocking and unovershadowing were assessed under forward and backward presentation conditions. Children also answered questions probing their ability to make the inference posited to be necessary for blocking by a reasoning account of cue competition. For the first time, children's working memory and general verbal ability were also measured alongside their causal learning. The magnitude of blocking and unovershadowing effects increased with age. However, analyses showed that the best predictor of both blocking and unovershadowing effects was children's performance on the reasoning questions. The magnitude of the blocking effect was also predicted by children's working memory abilities. These findings provide new evidence that cue competition effects such as blocking are underpinned by effortful reasoning processes. 

The Engine of Thought Is a Hybrid: Roles of Associative and Structured Knowledge in Reasoning

Across a range of domains in psychology different theories assume different mental representations of knowledge. For example, in the literature on category-based inductive reasoning, certain theories (e.g., Rogers & McClelland, 2004; Sloutsky & Fisher, 2008) assume that the knowledge upon which inductive inferences are based is associative, whereas others (e.g., Heit & Rubinstein, 1994; Kemp & Tenenbaum, 2009; Osherson, Smith, Wilkie, López, & Shafir, 1990) assume that knowledge is structured. In this article we investigate whether associative and structured knowledge underlie inductive reasoning to different degrees under different processing conditions. We develop a measure of knowledge about the degree of association between categories and show that it dissociates from measures of structured knowledge. In Experiment 1 participants rated the strength of inductive arguments whose categories were either taxonomically or causally related. A measure of associative strength predicted reasoning when people had to respond fast, whereas causal and taxonomic knowledge explained inference strength when people responded slowly. In Experiment 2, we also manipulated whether the causal link between the categories was predictive or diagnostic. Participants preferred predictive to diagnostic arguments except when they responded under cognitive load. In Experiment 3, using an open-ended induction paradigm, people generated and evaluated their own conclusion categories. Inductive strength was predicted by associative strength under heavy cognitive load, whereas an index of structured knowledge was more predictive of inductive strength under minimal cognitive load. Together these results suggest that associative and structured models of reasoning apply best under different processing conditions and that the application of structured knowledge in reasoning is often effortful.

Evidence reasoning for event inference in smart transport video surveillance

In this paper we present a new event recognition framework, based on the Dempster-Shafer theory of evidence, which combines the evidence from multiple atomic events detected by low-level computer vision analytics. The proposed framework employs evidential network modelling of composite events. This approach can effectively handle the uncertainty of the detected events, whilst inferring high-level events that have semantic meaning with high degrees of belief. Our scheme has been comprehensively evaluated against various scenarios that simulate passenger behaviour on public transport platforms such as buses and trains. The average accuracy rate of our method is 81% in comparison to 76% by a standard rule-based method.

Computing lower and upper expectations under epistemic independence

This paper investigates the computation of lower/upper expectations that must cohere with a collection of probabilistic assessments and a collection of judgements of epistemic independence. New algorithms, based on multilinear programming, are presented, both for independence among events and among random variables. Separation properties of graphical models are also investigated.

An Architecture of a Multi-Agent System for SCADA - Dealing With Uncertainty, Plans and Actions

This paper presents a multi-agent system approach to address the difficulties encountered in traditional SCADA systems deployed in critical environments such as electrical power generation, transmission and distribution. The approach models uncertainty and combines multiple sources of uncertain information to deliver robust plan selection. We examine the approach in the context of a simplified power supply/demand scenario using a residential grid connected solar system and consider the challenges of modelling and reasoning with
uncertain sensor information in this environment. We discuss examples of plans and actions required for sensing, establish and discuss the effect of uncertainty on such systems and investigate different uncertainty theories and how they can fuse uncertain information from multiple sources for effective decision making in
such a complex system.

An Ambiguity Aversion Framework of Security Game under Ambiguities

Security is a critical concern around the world. Since resources for security are always limited, lots of interest have arisen in using game theory to handle security resource allocation problems. However, most of the existing work does not address adequately how a defender chooses his optimal strategy in a game with absent, inaccurate, uncertain, and even ambiguous strategy profiles' payoffs. To address this issue, we propose a general framework of security games under ambiguities based on Dempster-Shafer theory and the ambiguity aversion principle of minimax regret. Then, we reveal some properties of this framework. Also, we present two methods to reduce the influence of complete ignorance. Our investigation shows that this new framework is better in handling security resource allocation problems under ambiguities.

Magnitude, form and bioavailability of fluvial carbon exports from Irish organic soils under pasture

Organic soils are widespread in Ireland and vulnerable to degradation via drainage for agriculture. The soil-landuse combination of pasture on organic soils may play a disproportionate role in regional C dynamics but is yet to receive study. Fluvial C fluxes and labile organic fractions were determined for two such sites at nested field (c.4 ha) and subcatchment scales (>40 ha); one relatively dry and nutrient rich, the other wetter and nutrient poor. Field scale flux from the nutrient poor site over 2 years was 38.9 ± 6.6 g C m⁻² yr⁻¹ with DIC > DOC > POC at 57, 32 and 11 % respectively, and 72 % DIC was comprised of above equilibrium CO₂. At the nutrient rich site, which overlies limestone geology, field scale export over an individual year was 90.4 g C m⁻² with DIC > DOC > POC at 49, 42 and 9 %, but with 90 % DIC as bicarbonate. By comparison with the nutrient poor site, the magnitude and composition of inorganic C exports from the nutrient rich site implied considerable export of soil-respiratory C as bicarbonate, and lower evasion losses due to carbonate system buffering. Labile DOC determined using dark incubations indicated small fractions (5–10 %) available for remineralisation over typical downstream transit times of days to weeks. These fractions are probably conservative as photolysis in the environment can increase the proportion of labile compounds via photocleavage and directly remineralise organic matter. This study demonstrates that monitoring at soil–water interfaces can aid capture of total landscape fluvial fluxes by precluding the need to incorporate prior C evasion, although rapid runoff responses at field scales can necessitate high resolution flow proportional, and hydrograph sampling to constrain uncertainty of flux estimates.

Electron-Impact Uncertainty Analysis and its Impact on Certain Temperature Diagnostics

In this study we calculate the electron-impact uncertainties in atomic data for direct ionization and recombination and investigate the role of these uncertainties on spectral diagnostics. We outline a systematic approach to assigning meaningful uncertainties that vary with electron temperature. Once these uncertainty parameters have been evaluated, we can then calculate the uncertainties on key diagnostics through a Monte Carlo routine, using the Astrophysical Emission Code (APEC) [Smith et al. 2001]. We incorporate these uncertainties into well known temperature diagnostics, such as the Lyman alpha versus resonance line ratio and the G ratio. We compare these calculations to a study performed by [Testa et al. 2004], where significant discrepancies in the two diagnostic ratios were observed. We conclude that while the atomic physics uncertainties play a noticeable role in the discrepancies observed by Testa, they do not explain all of them. This indicates that there is another physical process occurring in the system that is not being taken into account. This work is supported in part by the National Science Foundation REU and Department of Defense ASSURE programs under NSF Grant no. 1262851 and by the Smithsonian Institution.