Bayesian Learning and Predictability in a Stochastic Nonlinear Dynamical Model

Bayesian inference methods are applied within a Bayesian hierarchical modelling framework to the problems of joint state and parameter estimation, and of state forecasting. We explore and demonstrate the ideas in the context of a simple nonlinear marine biogeochemical model. A novel approach is proposed to the formulation of the stochastic process model, in which ecophysiological properties of plankton communities are represented by autoregressive stochastic processes. This approach captures the effects of changes in plankton communities over time, and it allows the incorporation of literature metadata on individual species into prior distributions for process model parameters. The approach is applied to a case study at Ocean Station Papa, using Particle Markov chain Monte Carlo computational techniques. The results suggest that, by drawing on objective prior information, it is possible to extract useful information about model state and a subset of parameters, and even to make useful long-term forecasts, based on sparse and noisy observations

Children with life-limiting conditions in paediatric intensive care units: a national cohort, data linkage study

Objective: To determine how many children are admitted to paediatric intensive care unit (PICU) with life-limiting conditions (LLCs) and their outcomes. Design: National cohort, data-linkage study. Setting: PICUs in England. Patients: Children admitted to a UK PICU (1 January 2004 and 31 March 2015) were identified in the Paediatric Intensive Care Audit Network dataset. Linkage to hospital episodes statistics enabled identification of children with a LLC using an International Classification of Diseases (ICD10) code list. Main outcome measures: Random-effects logistic regression was undertaken to assess risk of death in PICU. Flexible parametric survival modelling was used to assess survival in the year after discharge. Results: Overall, 57.6% (n=89 127) of PICU admissions and 72.90% (n=4821) of deaths in PICU were for an individual with a LLC. The crude mortality rate in PICU was 5.4% for those with a LLC and 2.7% of those without a LLC. In the fully adjusted model, children with a LLC were 75% more likely than those without a LLC to die in PICU (OR 1.75 (95% CI 1.64 to 1.87)). Although overall survival to 1 year postdischarge was 96%, children with a LLC were 2.5 times more likely to die in that year than children without a LLC (OR 2.59 (95% CI 2.47 to 2.71)). Conclusions: Children with a LLC accounted for a large proportion of the PICU population. There is an opportunity to integrate specialist paediatric palliative care services with paediatric critical care to enable choice around place of care for these children and families

Understanding your digital identity

The term “Digital Identity” is used here to describe the persona a person projects across the internet. Your Digital Identity as perceived by other people is made up of material that you post yourself (for example photographs on Flickr and your own web page) but it also is made up of material other people put there about you (blog posts that mention you, photographs in which you are tagged). The “This is Me” project has developed resources that can be used by students and others to appreciate what their Digital Identity is and how they can control it to help present the persona with the reputation that they want

A feasibility study of signed consent for the collection of patient identifiable information for a national paediatric clinical audit database

Objectives: To investigate the feasibility of obtaining signed consent for submission of patient identifiable data to a national clinical audit database and to identify factors influencing the consent process and its success. Design: Feasibility study. Setting: Seven paediatric intensive care units in England. Participants: Parents/guardians of patients, or patients aged 12-16 years old, approached consecutively over three months for signed consent for submission of patient identifiable data to the national clinical audit database the Paediatric Intensive Care Audit Network (PICANet). Main outcome measures: The numbers and proportions of admissions for which signed consent was given, refused, or not obtained (form not returned or form partially completed but not signed), by age, sex, level of deprivation, ethnicity (South Asian or not), paediatric index of mortality score, length of hospital stay (days in paediatric intensive care). Results: One unit did not start and one did not fully implement the protocol, so analysis excluded these two units. Consent was obtained for 182 of 422 admissions (43%) (range by unit 9% to 84%). Most (101/182; 55%) consents were taken by staff nurses. One refusal (0.2%) was received. Consent rates were significantly better for children who were more severely ill on admission and for hospital stays of six days or more, and significantly poorer for children aged 10-14 years. Long hospital stays and children aged 10-14 years remained significant in a stepwise regression model of the factors that were significant in the univariate model. Conclusion: Systematically obtaining individual signed consent for sharing patient identifiable information with an externally located clinical audit database is difficult. Obtaining such consent is unlikely to be successful unless additional resources are specifically allocated to training, staff time, and administrative support

A Low Cost Magnetic Resonance Relaxometry Sensor

Magnetic resonance relaxometry, conducted by measuring relaxation parameters at different field strengths, has become an increasingly popular technique in recent years. This technique, known as field cycling, often uses expensive and large electromagnets. In this work we present a small, portable field cycling sensor. Fast field cycling is a technique that uses a varying magnetic field applied to a sample, polarising it at a high field, allowing it time to develop at a lower field and then collecting the data at the same initial high field. This causes changes in T1 and can reveal interesting proper ties of the samples not seen by traditional methods. A prototype portable magnetic resonance sensor that undertakes relaxometry measurements using fast field cycling has been developed using a combination of permanent magnets which has been used to conduct preliminary studies on a water sample. We demonstrate the effectiveness of this sensor by conducting measurements of T1 at different field strengths

Dropout: MOOC participants’perspective

Massive Open Online Courses (MOOCs) open up learning opportunities to a large number of people. A small percentage (around 10%) of the large numbers of participants enrolling in MOOCs manage to finish the course by completing all parts. The term ‘dropout’ is commonly used to refer to ‘all who failed to complete’ a course, and is used in relation to MOOCs. Due to the nature of MOOCs, with students not paying enrolment and tuition fees, there is no direct financial cost incurred by a student. Therefore it is debatable whether the traditional definition of dropout in higher education could be directly applied to MOOCs. This paper reports ongoing exploratory work on MOOC participants’ perspectives based on six qualitative interviews. The findings show that MOOC participants are challenging the widely held view of dropout, suggesting that it is more about failing to achieve their personal aims