Terrorist transgressions: gendered representations of the terrorist in visual culture

The aim of Terrorist Transgressions is to analyse the myths inscribed in images of the terrorist and identify how agency is attributed to representation through invocations and inversions of gender stereotypes. In modern discourses on the terrorist the horror experienced in Western societies was the appearance of a new sense of the vulnerability of the body politic, and therefore of the modern self with its direct dependency on security and property. The terrorist has been constructed as the epitome of transgression against economic resources and moral, physical and political boundaries. Although terrorism has been the focus of intense academic activity, cultural representations of the terrorist have received less attention. Yet terrorism is dependent on spectacle and the topic is subject to forceful exposure in popular media. While the terrorist is predominantly aligned with masculinity, women have been active in terrorist organisations since the late 19th century and in suicidal terrorist attacks since the 1980s. Such attacks have confounded constructions of femininity and masculinity, with profound implications for the gendering of violence and horror. The publication arises from an AHRC networking grant, 2011-12, with Birkbeck, and includes collaboration with the army at Sandhurst RMA. The project relates to a wider investigation into feminism, violence and contemporary art.

Socially anxious mothers’ narratives to their children, and their relation to child representations and adjustment

Anxious mothers’ parenting, particularly transfer of threat information, has been considered important in their children’s risk for social anxiety disorder (SAnxD), and maternal narratives concerning potential social threat could elucidate this contribution. Maternal narratives to their pre-school 4-5 year-old children, via a picture book about starting school, were assessed in socially anxious (N=73), and non-anxious (N=63) mothers. Child representations of school were assessed via Doll Play (DP). After one school term, mothers (CBCL) and teachers (TRF) reported on child internalizing problems, and child SAnxD was assessed via maternal interview. Relations between these variables, infant behavioral inhibition, and attachment, were examined. Socially anxious mothers showed more negative (higher threat attribution), and less supportive (lower encouragement) narratives, than controls, and their children’s DP representations, SAnxD and CBCL scores were more adverse. High narrative threat predicted child SAnxD; lower encouragement predicted negative child CBCL scores and, particularly for behaviorally inhibited children, TRF scores and DP representations. In securely attached children, CBCL scores and risk for SAnxD were affected by maternal anxiety and threat attributions, respectively. Low encouragement mediated the effects of maternal anxiety on child DP representations, and CBCL scores. Maternal narratives are affected by social anxiety, and contribute to adverse child outcome.

Enhanced affective brain representations of chocolate in cravers vs. non-cravers

To examine the neural circuitry involved in food craving, in making food particularly appetitive and thus in driving wanting and eating, we used fMRI to measure the response to the flavour of chocolate, the sight of chocolate and their combination in cravers vs. non-cravers. Statistical parametric mapping (SPM) analyses showed that the sight of chocolate produced more activation in chocolate cravers than non-cravers in the medial orbitofrontal cortex and ventral striatum. For cravers vs. non-cravers, a combination of a picture of chocolate with chocolate in the mouth produced a greater effect than the sum of the components (i.e. supralinearity) in the medial orbitofrontal cortex and pregenual cingulate cortex. Furthermore, the pleasantness ratings of the chocolate and chocolate-related stimuli had higher positive correlations with the fMRI blood oxygenation level-dependent signals in the pregenual cingulate cortex and medial orbitofrontal cortex in the cravers than in the non-cravers. To our knowledge, this is the first study to show that there are differences between cravers and non-cravers in their responses to the sensory components of a craved food in the orbitofrontal cortex, ventral striatum and pregenual cingulate cortex, and that in some of these regions the differences are related to the subjective pleasantness of the craved foods. Understanding individual differences in brain responses to very pleasant foods helps in the understanding of the mechanisms that drive the liking for specific foods and thus intake of those foods.

Expected value, reward outcome, and temporal difference error representations in a probabilistic decision task

In probabilistic decision tasks, an expected value (EV) of a choice is calculated, and after the choice has been made, this can be updated based on a temporal difference (TD) prediction error between the EV and the reward magnitude (RM) obtained. The EV is measured as the probability of obtaining a reward x RM. To understand the contribution of different brain areas to these decision-making processes, functional magnetic resonance imaging activations related to EV versus RM (or outcome) were measured in a probabilistic decision task. Activations in the medial orbitofrontal cortex were correlated with both RM and with EV and confirmed in a conjunction analysis to extend toward the pregenual cingulate cortex. From these representations, TD reward prediction errors could be produced. Activations in areas that receive from the orbitofrontal cortex including the ventral striatum, midbrain, and inferior frontal gyrus were correlated with the TD error. Activations in the anterior insula were correlated negatively with EV, occurring when low reward outcomes were expected, and also with the uncertainty of the reward, implicating this region in basic and crucial decision-making parameters, low expected outcomes, and uncertainty.

Semantic self-knowledge and episodic self-knowledge: Independent or interrelated representations?

In this study of the structure of self-knowledge, we examined priming effects for the recall of personal episodes in order to investigate whether abstract trait knowledge and personal episodes are independent mental representations. We found that accessing similar abstract representations of traits facilitated a faster recall of related personal episodes than did accessing irrelevant abstract representations of traits (Experiments 1 and 2), reading a nonword prime (Experiments 2 and 3), accessing knowledge of one's mother (Experiment 3), or accessing semantic knowledge (Experiment 3). Contrary to previous findings, which indicated that abstract trait knowledge is represented independently of related personal episodes (e.g., Klein & Loftus, 1993, our results suggest that abstract trait knowledge is associated with personal episodes, and therefore that semantic self-knowledge is associated with episodic self-knowledge in long-term self-knowledge.

The absent body: representations of dying early modern women in a selection of seventeenth-century diaries

This article seeks to explore the absence of the body in the depiction of dying women in a selection of seventeenth-century diaries. It considers the cultural forces that made this absence inevitable, and the means by which the physical body was replaced in death by a spiritual presence. The elevation of a dying woman from physical carer to spiritual nurturer in the days before death ensured that gender codes were not broken. The centrality of the body of the dying woman, within a female circle of care and support, was paradoxically juxtaposed with an effacement of the body in descriptions of a good death. In death, a woman might achieve the stillness, silence and compliance so essential to perfect early modern womanhood, and retrospective diary entries can achieve this ideal by replacing the body with images that deflect from the essential physicality of the woman.

Sparse density estimation on the multinomial manifold

A new sparse kernel density estimator is introduced based on the minimum integrated square error criterion for the finite mixture model. Since the constraint on the mixing coefficients of the finite mixture model is on the multinomial manifold, we use the well-known Riemannian trust-region (RTR) algorithm for solving this problem. The first- and second-order Riemannian geometry of the multinomial manifold are derived and utilized in the RTR algorithm. Numerical examples are employed to demonstrate that the proposed approach is effective in constructing sparse kernel density estimators with an accuracy competitive with those of existing kernel density estimators.

Joint multiple dictionary learning for tensor sparse coding

Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form —a tensor— by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

Advances in the stochastic modelling of satellite-derived rainfall estimates using a sparse calibration dataset

As satellite technology develops, satellite rainfall estimates are likely to become ever more important in the world of food security. It is therefore vital to be able to identify the uncertainty of such estimates and for end users to be able to use this information in a meaningful way. This paper presents new developments in the methodology of simulating satellite rainfall ensembles from thermal infrared satellite data. Although the basic sequential simulation methodology has been developed in previous studies, it was not suitable for use in regions with more complex terrain and limited calibration data. Developments in this work include the creation of a multithreshold, multizone calibration procedure, plus investigations into the causes of an overestimation of low rainfall amounts and the best way to take into account clustered calibration data. A case study of the Ethiopian highlands has been used as an illustration.

A comparative corpus-assisted discourse study of the representations of hosts in promotional tourism discourse

Most studies concerned with the representations of local people in tourism discourse point to the prevalence of stereotypic images asserting that contemporary tourism perpetuates colonial legacy and gendered discursive practices. This claim has been, to some extent, contested in research that explores representations of hosts in local tourism materials claiming that tourism can also discursively resist the dominant Western imagery. While the evidence for the existence of hegemonic and diverging discourses about the local ‘Other’ seems compelling, the empirical basis of this research is rather small and often limited to one geographic context. The present study addresses these shortcomings by examining representations of hosts in a larger corpus of promotional tourism materials including texts produced by Western and local tourism industries. The data is investigated using the methodology of Corpus-Assisted Discourse Studies (CADS). By comparing external with internal (self) representations, this study verifies and refines some of the claims on the subject and offers a much more nuanced picture of representations that defies the black and white scenarios proposed in previous research

Sparse space-time boundary element methods for the heat equation

The goal of this work is the efficient solution of the heat equation with Dirichlet or Neumann boundary conditions using the Boundary Elements Method (BEM). Efficiently solving the heat equation is useful, as it is a simple model problem for other types of parabolic problems. In complicated spatial domains as often found in engineering, BEM can be beneficial since only the boundary of the domain has to be discretised. This makes BEM easier than domain methods such as finite elements and finite differences, conventionally combined with time-stepping schemes to solve this problem. The contribution of this work is to further decrease the complexity of solving the heat equation, leading both to speed gains (in CPU time) as well as requiring smaller amounts of memory to solve the same problem. To do this we will combine the complexity gains of boundary reduction by integral equation formulations with a discretisation using wavelet bases. This reduces the total work to O(h

Intersections and differentiations: a corpus-assisted discourse study of gender representations in the British press before, during and after the London Olympics 2012

This study examines the impact of a global sports event on gender representations in media reporting. Whereas previous research on gender, sport and media has been mainly concerned with sports events in the North American or Australian context, this study investigates the British media reporting before, during and after the London Olympics 2012. Our study follows the approach of Corpus-Assisted Discourse Studies (CADS) and uses both quantitative and qualitative research procedures. The results reveal more balanced gender representations during the London Olympics in that the ‘regular’ biased associations were supressed in favour of positive references to female achievements. However, little carry-though of the ‘gains’ was noted. Also, this study shows that the positive associations intersected with national sentiments and were used to celebrate the nation-state. At the same time, some subtle resistance was observed to accepting as ‘truly’ British the non-white athletes and those not born in Britain.

Simulating decadal variability in the North Atlantic Ocean

Observations and climate models suggest significant decadal variability within the North Atlantic subpolar gyre (NA SPG), though observations are sparse and models disagree on the details of this variability. Therefore, it is important to understand 1) the mechanisms of simulated decadal variability, 2) which parts of simulated variability are more faithful representations of reality, and 3) the implications for climate predictions. Here, we investigate the decadal variability in the NA SPG in the state-of-the-art, high resolution (0.25◦ ocean resolution), climate model ‘HadGEM3’. We find a decadal mode with a period of 17 years that explains 30% of the annual variance in related indices. The mode arises due to the advection of heat content anomalies, and shows asymmetries in the timescale of phase reversal between positive and negative phases. A negative feedback from temperature-driven density anomalies in the Labrador Sea (LS) allows for the phase reversal. The North Atlantic Oscillation (NAO), which exhibits the same periodicity, amplifies the mode. The atmosphere-ocean coupling is stronger during positive rather than negative NAO states, explaining the asymmetry. Within the NA SPG, there is potential predictability arising partly from this mode for up to 5 years. There are important similarities between observed and simulated variability, such as the apparent role for the propagation of heat content anomalies. However, observations suggest interannual LS density anomalies are salinity-driven. Salinity control of density would change the temperature feedback to the south, possibly limiting real-world predictive skill in the southern NA SPG with this model. Finally, to understand the diversity of behaviours, we analyse 42 present-generation climate models. Temperature and salinity biases are found to systematically influence the driver of density variability in the LS. Resolution is a good predictor of the biases. The dependence of variability on the background state has important implications for decadal predictions.