Low complexity method for large-scale self-consistent ab initio electronic-structure calculations without localization

A novel low complexity method to perform self-consistent electronic-structure calculations using the Kohn-Sham formalism of density functional theory is presented. Localization constraints are neither imposed nor required thereby allowing direct comparison with conventional cubically scaling algorithms. The method has, to date, the lowest complexity of any algorithm for an exact calculation. A simple one-dimensional model system is used to thoroughly test the numerical stability of the algorithm and results for a real physical system are also given

Arabic dialect identification in the context of bivalency and code-switching

In this paper we use a novel approach towards Arabic dialect identification using language bivalency and written code-switching. Bivalency between languages or dialects is where a word or element is treated by language users as having a fundamentally similar semantic content in more than one language or dialect. Arabic dialect identification in writing is a difficult task even for humans due to the fact that words are used interchangeably between dialects. The task of automatically identifying dialect is harder and classifiers trained using only n-grams will perform poorly when tested on unseen data. Such approaches require significant amounts of annotated training data which is costly and time consuming to produce. Currently available Arabic dialect datasets do not exceed a few hundred thousand sentences, thus we need to extract features other than word and character n-grams. In our work we present experimental results from automatically identifying dialects from the four main Arabic dialect regions (Egypt, North Africa, Gulf and Levant) in addition to Standard Arabic. We extend previous work by incorporating additional grammatical and stylistic features and define a subtractive bivalency profiling approach to address issues of bivalent words across the examined Arabic dialects. The results show that our new methods classification accuracy can reach more than 76% and score well (66%) when tested on completely unseen data

The REVERE project:Experiments with the application of probabilistic NLP to systems engineering

Despite natural language’s well-documented shortcomings as a medium for precise technical description, its use in software-intensive systems engineering remains inescapable. This poses many problems for engineers who must derive problem understanding and synthesise precise solution descriptions from free text. This is true both for the largely unstructured textual descriptions from which system requirements are derived, and for more formal documents, such as standards, which impose requirements on system development processes. This paper describes experiments that we have carried out in the REVERE1 project to investigate the use of probabilistic natural language processing techniques to provide systems engineering support

Isis: protecting children in online social networks

The aim of the Isis project is to develop an ethics-centred monitoring framework and tools for supporting law enforcement agencies in policing online social networks for the purpose of protecting children. The project is developing natural language analysis techniques to help identify child sex offenders from chat logs and monitoring mechanisms that can be noninvasively attached to file sharing systems for identifying the distributors of child abuse media. The ethical issues associated with such monitoring activities are studied through consultations with representatives from stakeholder communities and fed back into the development of the framework and tools. The project results are to be used and evaluated by specialist international law enforcement agencies as part of their own policing activities

The interaction of class and gender in illness narratives

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 BSA Publications Ltd.Perspectives on gender and identity that emphasize variability of performance, local context and individual agency have displaced earlier paradigms.These are now perceived to have supported gender stereotypes and language ideologies by emphasizing gender difference and homogeneity within genders. In a secondary analysis of health and illness narratives we explore the interaction of class and gender in individuals' constructions of gendered identity. High social class men perform gender in particularly varied ways and we speculate that this variable repertoire, including the use of what was once termed `women's language', is linked to a capacity to maintain social distinction and authority. Men's performance of conventional masculinity is often threatened by both the experience of illness and being interviewed about personal experience. Lower social class women in particular demonstrate an intensification of a pre-existing informal family and support group culture, marking successful members by awarding them the accolade of being `lovely'.ESR

Early social adversity modulates the relation between attention biases and socioemotional behaviour in juvenile macaques

Affect-biased attention may play a fundamental role in early socioemotional development, but factors influencing its emergence and associations with typical versus pathological outcomes remain unclear. Here, we adopted a nonhuman primate model of early social adversity (ESA) to: (1) establish whether juvenile, pre-adolescent macaques demonstrate attention biases to both threatening and reward-related dynamic facial gestures; (2) examine the effects of early social experience on such biases; and (3) investigate how this relation may be linked to socioemotional behaviour. Two groups of juvenile macaques (ESA exposed and non-ESA exposed) were presented with pairs of dynamic facial gestures comprising two conditions: neutral-threat and neutral-lipsmacking. Attention biases to threat and lipsmacking were calculated as the proportion of gaze to the affective versus neutral gesture. Measures of anxiety and social engagement were also acquired from videos of the subjects in their everyday social environment. Results revealed that while both groups demonstrated an attention bias towards threatening facial gestures, a greater bias linked to anxiety was demonstrated by the ESA group only. Only the non-ESA group demonstrated a significant attention bias towards lipsmacking, and the degree of this positive bias was related to duration and frequency of social engagement in this group. These findings offer important insights into the effects of early social experience on affect-biased attention and related socioemotional behaviour in nonhuman primates, and demonstrate the utility of this model for future investigations into the neural and learning mechanisms underlying this relationship across development