Realising the full potential of primary care: uniting the ‘two faces’ of generalism

Faced with an unprecedented mismatch between presented health needs and resources available, we must rethink both how we deliver healthcare and what care we deliver. Work has already started on the ‘how’: notably with efforts to strengthen access and integration (improved coordination of the comprehensive care needed to meet a diverse range of needs). It is defining ‘what’ to deliver that is proving more challenging. To address emerging problems of over- and under-treatment associated with the undue specialisation of healthcare, we need to strengthen delivery of generalist medical care. Meaning we need to bolster capacity to decide if and when medical intervention is the right approach for this individual (whole person) in their lived context. We need to put the interpretive expertise of the medical generalist back at the core of our primary healthcare systems

Generating walking behaviours in legged robots

Many legged robots have boon built with a variety of different abilities, from running to liopping to climbing stairs. Despite this however, there has been no consistency of approach to the problem of getting them to walk. Approaches have included breaking down the walking step into discrete parts and then controlling them separately, using springs and linkages to achieve a passive walking cycle, and even working out the necessary movements in simulation and then imposing them on the real robot. All of these have limitations, although most were successful at the task for which they were designed. However, all of them fall into one of two categories: either they alter the dynamics of the robots physically so that the robot, whilst very good at walking, is not as general purpose as it once was (as with the passive robots), or they control the physical mechanism of the robot directly to achieve their goals, and this is a difficult task.In this thesis a design methodology is described for building controllers for 3D dynam¬ ically stable walking, inspired by the best walkers and runners around — ourselves — so the controllers produced are based 011 the vertebrate Central Nervous System. This means that there is a low-level controller which adapts itself to the robot so that, when switched on, it can be considered to simulate the springs and linkages of the passive robots to produce a walking robot, and this now active mechanism is then controlled by a relatively simple higher level controller. This is the best of both worlds — we have a robot which is inherently capable of walking, and thus is easy to control like the passive walkers, but also retains the general purpose abilities which makes it so potentially useful.This design methodology uses an evolutionary algorithm to generate low-level control¬ lers for a selection of simulated legged robots. The thesis also looks in detail at previous walking robots and their controllers and shows that some approaches, including staged evolution and hand-coding designs, may be unnecessary, and indeed inappropriate, at least for a general purpose controller. The specific algorithm used is evolutionary, using a simple genetic algorithm to allow adaptation to different robot configurations, and the controllers evolved are continuous time neural networks. These are chosen because of their ability to entrain to the movement of the robot, allowing the whole robot and network to be considered as a single dynamical system, which can then be controlled by a higher level system.An extensive program of experiments investigates the types of neural models and net¬ work structures which are best suited to this task, and it is shown that stateless and simple dynamic neural models are significantly outperformed as controllers by more complex, biologically plausible ones but that other ideas taken from biological systems, including network connectivities, are not generally as useful and reasons for this are examined.The thesis then shows that this system, although only developed 011 a single robot, is capable of automatically generating controllers for a wide selection of different test designs. Finally it shows that high level controllers, at least to control steering and speed, can be easily built 011 top of this now active walking mechanism

Sparse Bayesian variable selection for the identification of antigenic variability in the Foot-and-Mouth disease virus

Vaccines created from closely related viruses are vital for offering protection against newly emerging strains. For Foot-and-Mouth disease virus (FMDV), where multiple serotypes co-circulate, testing large numbers of vaccines can be infeasible. Therefore the development of an in silico predictor of cross- protection between strains is important to help optimise vaccine choice. Here we describe a novel sparse Bayesian variable selection model using spike and slab priors which is able to predict antigenic variability and identify sites which are important for the neutralisation of the virus. We are able to iden- tify multiple residues which are known to be key indicators of antigenic variability. Many of these were not identified previously using frequentist mixed-effects models and still cannot be found when an ℓ1 penalty is used. We further explore how the Markov chain Monte Carlo (MCMC) proposal method for the inclusion of variables can offer significant reductions in computational requirements, both for spike and slab priors in general, and our hierarchical Bayesian model in particular

Families and work: revisiting barriers to employment

"In recent years, considerable effort has been put into supporting parents to make the transition into work. This study was commissioned by the Department for Work and Pensions (DWP) to explore whether these incentives were helping parents to overcome the barriers known to impede their engagement in the formal labour market. The report is based on fieldwork conducted in 2009. However, the concluding chapter considers the significance of the findings in light of proposals for the introduction of the Universal Credit and other reforms of the tax and benefit systems proposed by the Coalition Government." - Page 1

Facilitating Problem Framing in Project-Based Learning

While problem solving is a relatively well understood process, problem framing is less well understood, particularly with regard to supporting students to learn as they frame problems. Project-based learning classrooms are an ideal setting to investigate how teachers facilitate this process. Using participant observation, this study investigated how teachers supported students in taking ownership over the framing of problems in a charter school that serves students who have been underserved by traditional schooling. Data include audio/video records, field notes, interviews, and student work from a nineweek project. Interaction analysis was used to examine ownership and learning over time. Analysis suggests that providing a relevant yet revisable design problem, giving instruction about design process as iterative, and problematizing a model of design process supported students in taking ownership over the framing of the problem; students were motivated to pose questions and gathered information purposefully, thereby learning in the process

Estimating the potential impact of canine distemper virus on the Amur tiger population (Panthera tigris altaica) in Russia

Lethal infections with canine distemper virus (CDV) have recently been diagnosed in Amur tigers (Panthera tigris altaica), but long-term implications for the population are unknown. This study evaluates the potential impact of CDV on a key tiger population in Sikhote-Alin Biosphere Zapovednik (SABZ), and assesses how CDV might influence the extinction potential of other tiger populations of varying sizes. An individual-based stochastic, SIRD (susceptible-infected-recovered/dead) model was used to simulate infection through predation of infected domestic dogs, and/or wild carnivores, and direct tiger-to-tiger transmission. CDV prevalence and effective contact based on published and observed data was used to define plausible low- and high-risk infection scenarios. CDV infection increased the 50-year extinction probability of tigers in SABZ by 6.3% to 55.8% compared to a control population, depending on risk scenario. The most significant factors influencing model outcome were virus prevalence in the reservoir population(s) and its effective contact rate with tigers. Adjustment of the mortality rate had a proportional impact, while inclusion of epizootic infection waves had negligible additional impact. Small populations were found to be disproportionately vulnerable to extinction through CDV infection. The 50-year extinction risk in populations consisting of 25 individuals was 1.65 times greater when CDV was present than that of control populations. The effects of density dependence do not protect an endangered population from the impacts of a multi-host pathogen, such as CDV, where they coexist with an abundant reservoir presenting a persistent threat. Awareness of CDV is a critical component of a successful tiger conservation management policy