The representation of bodily pain in late nineteenth-century English culture

This book deals with bodily pain in the late Victorian period, considering the ways in which its understanding is shaped by medicine and theology.

Representation errors and retrievals in linear and nonlinear data assimilation

This article shows how one can formulate the representation problem starting from Bayes’ theorem. The purpose of this article is to raise awareness of the formal solutions,so that approximations can be placed in a proper context. The representation errors appear in the likelihood, and the different possibilities for the representation of reality in model and observations are discussed, including nonlinear representation probability density functions. Specifically, the assumptions needed in the usual procedure to add a representation error covariance to the error covariance of the observations are discussed,and it is shown that, when several sub-grid observations are present, their mean still has a representation error ; socalled ‘superobbing’ does not resolve the issue. Connection is made to the off-line or on-line retrieval problem, providing a new simple proof of the equivalence of assimilating linear retrievals and original observations. Furthermore, it is shown how nonlinear retrievals can be assimilated without loss of information. Finally we discuss how errors in the observation operator model can be treated consistently in the Bayesian framework, connecting to previous work in this area.

Instantaneous threat detection based on a semantic representation of activities, zones and trajectories

Threat detection is a challenging problem, because threats appear in many variations and differences to normal behaviour can be very subtle. In this paper, we consider threats on a parking lot, where theft of a truck’s cargo occurs. The threats range from explicit, e.g. a person attacking the truck driver, to implicit, e.g. somebody loitering and then fiddling with the exterior of the truck in order to open it. Our goal is a system that is able to recognize a threat instantaneously as they develop. Typical observables of the threats are a person’s activity, presence in a particular zone and the trajectory. The novelty of this paper is an encoding of these threat observables in a semantic, intermediate-level representation, based on low-level visual features that have no intrinsic semantic meaning themselves. The aim of this representation was to bridge the semantic gap between the low-level tracks and motion and the higher-level notion of threats. In our experiments, we demonstrate that our semantic representation is more descriptive for threat detection than directly using low-level features. We find that a person’s activities are the most important elements of this semantic representation, followed by the person’s trajectory. The proposed threat detection system is very accurate: 96.6 % of the tracks are correctly interpreted, when considering the temporal context.

The aims of early years outdoor education in England: a conceptual and empirical investigation

This paper explores the place of aims in the early years foundation stage outdoor environment in England. Through examining the writing of academics, various themes are identified, and constructed into possible aims. These themes/aims are compared to an empirical study of early years teachers’ attitudes. Data was collected by questionnaire from schools within the University of Reading partnership. There was general agreement between experts and teachers as to the aims. While some respondents were able to explain what the aims of outdoor activity were, a significant number were unable to identify aims; further, a significant number did not distinguish between approach/practice and aims. A lack of understanding and agreement as to what the aims are may indicate teachers are unsure about the purpose of outdoor education for young children. A result of this study is to agree and make explicit the aims for outdoor education in the early years.

The error of representation: basic understanding

Representation error arises from the inability of the forecast model to accurately simulate the climatology of the truth. We present a rigorous framework for understanding this kind of error of representation. This framework shows that the lack of an inverse in the relationship between the true climatology (true attractor) and the forecast climatology (forecast attractor) leads to the error of representation. A new gain matrix for the data assimilation problem is derived that illustrates the proper approaches one may take to perform Bayesian data assimilation when the observations are of states on one attractor but the forecast model resides on another. This new data assimilation algorithm is the optimal scheme for the situation where the distributions on the true attractor and the forecast attractors are separately Gaussian and there exists a linear map between them. The results of this theory are illustrated in a simple Gaussian multivariate model.

The representation of the West-African Monsoon vertical cloud structure in the Met Office Unified Model: an evaluation with CloudSat

Weather and climate model simulations of the West African Monsoon (WAM) have generally poor representation of the rainfall distribution and monsoon circulation because key processes, such as clouds and convection, are poorly characterized. The vertical distribution of cloud and precipitation during the WAM are evaluated in Met Office Unified Model simulations against CloudSat observations. Simulations were run at 40-km and 12-km horizontal grid length using a convection parameterization scheme and at 12-km, 4-km, and 1.5-km grid length with the convection scheme effectively switched off, to study the impact of model resolution and convection parameterization scheme on the organisation of tropical convection. Radar reflectivity is forward-modelled from the model cloud fields using the CloudSat simulator to present a like-with-like comparison with the CloudSat radar observations. The representation of cloud and precipitation at 12-km horizontal grid length improves dramatically when the convection parameterization is switched off, primarily because of a reduction in daytime (moist) convection. Further improvement is obtained when reducing model grid length to 4 km or 1.5 km, especially in the representation of thin anvil and mid-level cloud, but three issues remain in all model configurations. Firstly, all simulations underestimate the fraction of anvils with cloud top height above 12 km, which can be attributed to too low ice water contents in the model compared to satellite retrievals. Secondly, the model consistently detrains mid-level cloud too close to the freezing level, compared to higher altitudes in CloudSat observations. Finally, there is too much low-level cloud cover in all simulations and this bias was not improved when adjusting the rainfall parameters in the microphysics scheme. To improve model simulations of the WAM, more detailed and in-situ observations of the dynamics and microphysics targeting these non-precipitating cloud types are required.

Improved seasonal prediction of the hot summer of 2003 over Europe through better representation of uncertainty in the land surface

Methods to explicitly represent uncertainties in weather and climate models have been developed and refined over the past decade, and have reduced biases and improved forecast skill when implemented in the atmospheric component of models. These methods have not yet been applied to the land surface component of models. Since the land surface is strongly coupled to the atmospheric state at certain times and in certain places (such as the European summer of 2003), improvements in the representation of land surface uncertainty may potentially lead to improvements in atmospheric forecasts for such events. Here we analyse seasonal retrospective forecasts for 1981–2012 performed with the European Centre for Medium-Range Weather Forecasts’ (ECMWF) coupled ensemble forecast model. We consider two methods of incorporating uncertainty into the land surface model (H-TESSEL): stochastic perturbation of tendencies, and static perturbation of key soil parameters. We find that the perturbed parameter approach considerably improves the forecast of extreme air temperature for summer 2003, through better representation of negative soil moisture anomalies and upward sensible heat flux. Averaged across all the reforecasts the perturbed parameter experiment shows relatively little impact on the mean bias, suggesting perturbations of at least this magnitude can be applied to the land surface without any degradation of model climate. There is also little impact on skill averaged across all reforecasts and some evidence of overdispersion for soil moisture. The stochastic tendency experiments show a large overdispersion for the soil temperature fields, indicating that the perturbation here is too strong. There is also some indication that the forecast of the 2003 warm event is improved for the stochastic experiments, however the improvement is not as large as observed for the perturbed parameter experiment.

A conceptual framework for service system interaction

There is a growing research concern on how service ecosystems form and interact. This research thus aims to explore the service ecosystem formation and interaction as well as its underlying nature of value co-creation. This work develops an initial conceptual framework for assessing service system interactions that includes the various stages of value co-creation within ecosystem context. How the conceptual framework will further be developed and future plan are also presented.

Breaching the social contract: crises of democratic representation and patterns of extreme right party support

Why has the extreme right Greek Golden Dawn, a party with clear links to fascism experienced a rise defying all theories that claim that such a party is unlikely to win in post-WWII Europe? And, if we accept that economic crisis is an explanation for this, why has such a phenomenon not occurred in other countries that have similar conducive conditions, such as Portugal and Spain? This article addresses this puzzle by (a) carrying out a controlled comparison of Greece, Portugal and Spain and (b) showing that the rise of the extreme right is not a question of intensity of economic crisis. Rather it is the nature of the crisis, i.e. economic versus overall crisis of democratic representation that facilitates the rise of the extreme right. We argue that extreme right parties are more likely to experience an increase in their support when economic crisis culminates into an overall crisis of democratic representation. Economic crisis is likely to become a political crisis when severe issues of governability impact upon the ability of the state to fulfil its social contract obligations. This breach of the social contract is accompanied by declining levels of trust in state institutions, resulting in party system collapse.

Low rank representation on Riemannian manifold of symmetric positive definite matrices

Sparse coding aims to find a more compact representation based on a set of dictionary atoms. A well-known technique looking at 2D sparsity is the low rank representation (LRR). However, in many computer vision applications, data often originate from a manifold, which is equipped with some Riemannian geometry. In this case, the existing LRR becomes inappropriate for modeling and incorporating the intrinsic geometry of the manifold that is potentially important and critical to applications. In this paper, we generalize the LRR over the Euclidean space to the LRR model over a specific Rimannian manifold—the manifold of symmetric positive matrices (SPD). Experiments on several computer vision datasets showcase its noise robustness and superior performance on classification and segmentation compared with state-of-the-art approaches.

Reply to: punishing food: what brain activity can tell us about the representation of food in recovered anorexia nervosa

Eating disorders are characterized by aberrant cognitions and behaviors around food. We used a novel functional magnetic resonance imaging task in a sample of recovered anorexia nervosa subjects to study the neural response to both pleasant and aversive food tastes and pictures compared with a group of matched female subjects who had never had the disorder. We report that individuals recovered from anorexia nervosa have an increased neural response to rewarding and aversive food stimuli, in the form of chocolate (e.g., in the ventral striatum) and moldy strawberries (e.g., in the caudate).

The dark side of brand attachment: a conceptual framework of brand attachment's detrimental outcomes

Brand attachment recently has received great attention among practitioners and academics alike. Scholars consider brand attachment a key requisite in consumer-brand relationships that create favourable consumer behaviours such as positive brand attitudes and brand loyalty. Few studies, however, examine the detrimental outcomes of brand attachment. In this paper, we develop a conceptual framework that explores how brand attachment may explain detrimental consumer behaviours, such as oppositional brand loyalty and antibrand actions. We investigate consumers' trash-talking and schadenfreude in brand communities and their subsequent outcomes. Our framework reveals that the link between brand attachment and oppositional brand loyalty is driven by consumers' social identity and sense of rivalry. Furthermore, we put forward that brand attachment leads to anti-brand actions when relationships deteriorate. We identify two factors behind the deterioration: (1) companies' opportunism activities, and (2) incongruity between consumers' values and the brand's values. Theoretical and managerial implications are discussed arising from our emerging 'dark side' brand attachment framework.