Introduction to Children's Palliative Care

Children's Palliative Care requires a holistic, person centred approach which takes into account the needs not only of the child but also the whole family. This presentation gives a short introduction to Paediatric Palliative Care, introducing key concepts such as Advanced Care Plans (ACPs) and the Spectrum of Children's Palliative Care Needs described by Shaw, Brook and Randall (2012). The main categories of conditions with which children with palliative care needs may present, are defined by the RCPCH and Together for Short Lives. This talk was given to year 1 - 3 Specialist Trainees in Paediatrics but it may be of interest to undergraduate and postgraduate students in Nursing and Allied Health Professions

High Speed Phase-Resolved 2-d UBV Photometry of the Crab pulsar

We report a phase-resolved photometric and morphological analysis of UBV data of the Crab pulsar obtained with the 2-d TRIFFID high speed optical photometer mounted on the Russian 6m telescope. By being able to accurately isolate the pulsar from the nebular background at an unprecedented temporal resolution (1 \mu s), the various light curve components were accurately fluxed via phase-resolved photometry. Within the $UBV$ range, our datasets are consistent with the existing trends reported elsewhere in the literature. In terms of flux and phase duration, both the peak Full Width Half Maxima and Half Width Half Maxima decrease as a function of photon energy. This is similarly the case for the flux associated with the bridge of emission. Power-law fits to the various light curve components are as follows; \alpha = 0.07 \pm 0.19 (peak 1), \alpha = -0.06 \pm 0.19 (peak 2) and \alpha = -0.44 \pm 0.19 (bridge) - the uncertainty here being dominated by the integrated CCD photometry used to independently reference the TRIFFID data. Temporally, the main peaks are coincident to \le 10 \mu s although an accurate phase lag with respect to the radio main peak is compromised by radio timing uncertainties. The plateau on the Crab's main peak was definitively determined to be \leq 55 \mu s in extent and may decrease as a function of photon energy. There is no evidence for non-stochastic activity over the light curves or within various phase regions, nor is there evidence of anything akin to the giant pulses noted in the radio. Finally, there is no evidence to support the existence of a reported 60 second modulation suggested to be as a consequence of free precession.Comment: 13 pages, 12 figures, accepted for publication in Astronomy & Astrophysic

RESPOND – A patient-centred programme to prevent secondary falls in older people presenting to the emergency department with a fall: Protocol for a mixed methods programme evaluation.

Background Programme evaluations conducted alongside randomised controlled trials (RCTs) have potential to enhance understanding of trial outcomes. This paper describes a multi-level programme evaluation to be conducted alongside an RCT of a falls prevention programme (RESPOND). Objectives 1) To conduct a process evaluation in order to identify the degree of implementation fidelity and associated barriers and facilitators. 2) To evaluate the primary intended impact of the programme: participation in fall prevention strategies, and the factors influencing participation. 3) To identify the factors influencing RESPOND RCT outcomes: falls, fall injuries and ED re-presentations. Methods/ Design Five hundred and twenty eight community-dwelling adults aged 60–90 years presenting to two EDs with a fall will be recruited and randomly assigned to the intervention or standard care group. All RESPOND participants and RESPOND clinicians will be included in the evaluation. A mixed methods design will be used and a programme logic model will frame the evaluation. Data will be sourced from interviews, focus groups, questionnaires, clinician case notes, recruitment records, participant-completed calendars, hospital administrative datasets, and audio-recordings of intervention contacts. Quantitative data will be analysed via descriptive and inferential statistics and qualitative data will be interpreted using thematic analysis. Discussion The RESPOND programme evaluation will provide information about contextual and influencing factors related to the RCT outcomes. The results will assist researchers, clinicians, and policy makers to make decisions about future falls prevention interventions. Insights gained are likely to be transferable to preventive health programmes for a range of chronic conditions

Optimal Allocation and Scheduling of Irrigation Water for Cotton and Soybeans

This study evaluated alternative irrigation scheduling strategies for cotton and soybean production on Sharkey clay soils in southeast Arkansas. Strategies were ranked on the basis of two basic criteria: expected net revenue and risk efficiency. Risk efficiency was defined for different risk preferences using stochastic dominance techniques. Preferred strategies for cotton employed tensiometer thresholds between -.45 atm and -.75 atm. Risk efficient soybean irrigation strategies varied with the degree of risk aversion--more risk averse decision makers prefer strategies with lower thresholds

An open-data, agent-based model of alcohol related crime

The allocation of resources to challenge city centre violent crime traditionally relies on historical data to identify hot-spots. The usefulness of such data-driven approaches is limited when historical data is scarce or unavailable (e.g. planning of a new city) or insufficiently representative (e.g. does not account for novel events, such as Olympic Games). In some cities, crime data is not systematically accumulated at all. We present a graph-constrained agent based simulation model of alcohol-related violent crime that is capable of predicting areas of likely violent crime without requiring any historical data. The only inputs to our simulation are publicly available geographical data, which makes our method immediately applicable to a wide range of tasks, such as optimal city planning, police patrol optimisation, devising alcohol licensing policies. In experiments, we evaluate our model and demonstrate agreement of our model's predictions on where and when violence will occur with real-world violent crime data. Analyses indicate that our agent based model may be able to make a significant contribution to attempts to prevent violence through deterrence or by design

Association of violence with urban points of interest

The association between alcohol outlets and violence has long been recognised, and is commonly used to inform policing and licensing policies (such as staggered closing times and zoning). Less investigated, however, is the association between violent crime and other urban points of interest, which while associated with the city centre alcohol consumption economy, are not explicitly alcohol outlets. Here, machine learning (specifically, LASSO regression) is used to model the distribution of violent crime for the central 9 km2 of ten large UK cities. Densities of 620 different Point of Interest types (sourced from Ordnance Survey) are used as predictors, with the 10 most explanatory variables being automatically selected for each city. Cross validation is used to test generalisability of each model. Results show that the inclusion of additional point of interest types produces a more accurate model, with significant increases in performance over a baseline univariate alcohol-outlet only model. Analysis of chosen variables for city-specific models shows potential candidates for new strategies on a per-city basis, with combined-model variables showing the general trend in POI/violence association across the UK. Although alcohol outlets remain the best individual predictor of violence, other points of interest should also be considered when modelling the distribution of violence in city centres. The presented method could be used to develop targeted, city-specific initiatives that go beyond alcohol outlets and also consider other locations

A smartphone app to assist smoking cessation among aboriginal Australians: Findings from a pilot randomized controlled trial

© David Peiris, Lachlan Wright, Madeline News, Kris Rogers, Julie Redfern, Clara Chow, David Thomas. Background: Mobile health (mHealth) apps have the potential to increase smoking cessation, but little research has been conducted with Aboriginal communities in Australia. Objective: We conducted a pilot study to assess the feasibility and acceptability and explore the effectiveness of a novel mHealth app to assist Aboriginal people to quit smoking. Methods: A pilot randomized controlled trial (RCT) and process evaluation comprising usage analytics data and in-depth interviews was conducted. Current Aboriginal smokers (>16 years old), who were willing to make a quit attempt in the next month, were recruited from Aboriginal Community Controlled Health Services and a government telephone coaching service. The intervention was a multifaceted Android or iOS app comprising a personalized profile and quit plan, text and in-app motivational messages, and a challenge feature allowing users to compete with others. The comparator was usual cessation support services. Outcome data collection and analysis were conducted blinded to treatment allocation. The primary outcome was self-reported continuous smoking abstinence verified by carbon monoxide breath testing at 6 months. Secondary outcomes included point prevalence of abstinence and use of smoking cessation therapies and services. Results: A total of 49 participants were recruited. Competing service delivery priorities, the lack of resources for research, and lack of support for randomization to a control group were the major recruitment barriers. At baseline, 23/49 (47%) of participants had tried to quit in recent weeks. At 6-month follow-up, only 1 participant (intervention arm) was abstinent. The process evaluation highlighted low to moderate app usage (3-10 new users per month and 4-8 returning users per month), an average of 2.9 sessions per user per month and 6.3 min per session. Key themes from interviews with intervention participants (n=15) included the following: (1) the powerful influence of prevailing social norms around acceptability of smoking; (2) high usage of mobile devices for phone, text, and social media but very low use of other smartphone apps; (3) the role of family and social group support in supporting quit attempts; and (4) low awareness and utilization of smoking cessation support services. Despite the broad acceptability of the app, participants also recommended technical improvements to improve functionality, greater customization of text messages, integration with existing social media platforms, and gamification features. Conclusions: Smoking cessation apps need to be integrated with commonly used functions of mobile phones and draw on social networks to support their use. Although they have the potential to increase utilization of cessation support services and treatments, more research is needed to identify optimal implementation models. Robust evaluation is critical to determine their impact; however, an RCT design may not be feasible in this setting. Trial Registration: Australian and New Zealand Clinical Trials Registry ACTRN12616001550493; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371792 (Archived by WebCite at http://www.webcitation.org/76TiV7HA6)

FLORA: a novel method to predict protein function from structure in diverse superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues