Alzheimer’s disease and the eye

Dementia, including Alzheimer’s disease (AD), is a major disorder causing visual problems in the elderly population. The pathology of AD includes the deposition in the brain of abnormal aggregates of ß-amyloid (Aß) in the form of senile plaques (SP) and abnormally phosphorylated tau in the form of neurofibrillary tangles (NFT). A variety of visual problems have been reported in patients with AD including loss of visual acuity (VA), colour vision and visual fields; changes in pupillary response to mydriatics, defects in fixation and in smooth and saccadic eye movements; changes in contrast sensitivity and in visual evoked potentials (VEP); and disturbances of complex visual functions such as reading, visuospatial function, and in the naming and identification of objects. Many of these changes are controversial with conflicting data in the literature and no ocular or visual feature can be regarded as particularly diagnostic of AD. In addition, some pathological changes have been observed to affect the eye, visual pathway, and visual cortex in AD. The optometrist has a role in helping a patient with AD, if it is believed that signs and symptoms of the disease are present, so as to optimize visual function and improve the quality of life. (J Optom 2009;2:103-111 ©2009 Spanish Council of Optometry)

Evaluating the appropriateness of speech input in marine applications : a field evaluation

This paper discusses the first of three studies which collectively represent a convergence of two ongoing research agendas: (1) the empirically-based comparison of the effects of evaluation environment on mobile usability evaluation results; and (2) the effect of environment - in this case lobster fishing boats - on achievable speech-recognition accuracy. We describe, in detail, our study and outline our results to date based on preliminary analysis. Broadly speaking, the potential for effective use of speech for data collection and vessel control looks very promising - surprisingly so! We outline our ongoing analysis and further work.

Special issue:key debates in the translation of advertising material

Much has been written about the marketing aspects of promotional material in general, and several scholars (particularly in linguistics) have addressed questions relating to the structure and function of advertisements, focusing on images, rhetorical structure, semiotic functions, discourse features and audio-visual media, amongst other aspects of the genre. Not much, on the other hand, has been written within translation studies about the complexities involved in the transfer of an advertising message. Contributors to this volume explore various interdependent aspects of the interlingual and intercultural transfer of an advertising message. They emphasize features of culture specificity, of multi-medial semiotic interaction, of values and stereotypes, and most importantly, they recommend strategies and approaches to assist translators. Topics covered include a critique of the Western-based approach to advertising in the context of the Far East; different perceptions of the concept of cleanliness in advertising texts in Italy, Russia and the UK; the Walls Cornetto strategy of internationalization of product appeal, followed by localization; the role of the translator in recreating appeal in different lingua-cultural contexts; what constitutes 'Italianness' in advertisements for British consumers; and strategies for repackaging France as a tourist destination.

Evaluating the appropriateness of speech input in marine applications:a field evaluation

This paper discusses the first of three studies which collectively represent a convergence of two ongoing research agendas: (1) the empirically-based comparison of the effects of evaluation environment on mobile usability evaluation results; and (2) the effect of environment - in this case lobster fishing boats - on achievable speech-recognition accuracy. We describe, in detail, our study and outline our results to date based on preliminary analysis. Broadly speaking, the potential for effective use of speech for data collection and vessel control looks very promising - surprisingly so! We outline our ongoing analysis and further work.

Politeness in computer-mediated discourse of a virtual team

Drawing on the newest findings of politeness research, this paper proposes an interactionally grounded approach to computer-mediated discourse (CMD). Through the analysis of naturally occurring text-based synchronous interactions of a virtual team the paper illustrates that the interactional politeness approach can account for linguistic phenomena not yet fully explored in computer-mediated discourse analysis. Strategies used for compensating for the lack of audio-visual information in computer-mediated communication, strategies to compensate for the technological constraints of the medium, and strategies to aid interaction management are examined from an interactional politeness viewpoint and compared to the previous findings of CMD analysis. The conclusion of this preliminary research suggests that the endeavour to communicate along the lines of politeness norms in a work-based virtual environment contradicts some of the previous findings of CMD research (unconventional orthography, capitalization, economizing), and that other areas (such as emoticons, backchannel signals and turn-taking strategies) need to be revisited and re-examined from an interactional perspective to fully understand how language functions in this merely text-based environment.

Spatial ecological complexity measures in GRASS GIS

Good estimates of ecosystem complexity are essential for a number of ecological tasks: from biodiversity estimation, to forest structure variable retrieval, to feature extraction by edge detection and generation of multifractal surface as neutral models for e.g. feature change assessment. Hence, measuring ecological complexity over space becomes crucial in macroecology and geography. Many geospatial tools have been advocated in spatial ecology to estimate ecosystem complexity and its changes over space and time. Among these tools, free and open source options especially offer opportunities to guarantee the robustness of algorithms and reproducibility. In this paper we will summarize the most straightforward measures of spatial complexity available in the Free and Open Source Software GRASS GIS, relating them to key ecological patterns and processes.

Deconstruction-analysis-explanation:contextualization in professional digital discourse

It is already a truism that emerging communication technologies have changed the landscape of communication in every aspect of our lives, but this is specifically true for how we communicate at work. Advances in communication technologies have enabled a wide range of digital communication modes to be utilized for both internal and external business communication; including audio and visual communication and voice-over protocols, as well as text-based channels, such as email, forums, instant messaging and social media. In spite of the wide range of available audio-visual channels, and despite the ever-increasing popularity of email, real-time text-based communication technologies (instant messaging or IM) are also on the rise (see Mak, 2014; Pazos et al., 2013; Radicati & Levenstein, 2013; and Markman in this volume). The prominence of IM is evident in the rise of this mode of communication, not only as a tool for internal business communication, but as a front-stage channel, particularly for customer service encounters or professional-client conversations (Makarem et al., 2009; Pearce et al., 2013; L. Zhang et al., 2011).

Writing online:a guide to effective digital communication at work

Online writing plays a complex and increasingly prominent role in the life of organizations. From newsletters to press releases, social media marketing and advertising, to virtual presentations and interactions via e-mail and instant messaging, digital writing intertwines and affects the day-to-day running of the company - yet we rarely pay enough attention to it. Typing on the screen can become particularly problematic because digital text-based communication increases the opportunities for misunderstanding: it lacks the direct audio-visual contact and the norms and conventions that would normally help people to understand each other. Providing a clear, convincing and approachable discussion, this book addresses arenas of online writing: virtual teamwork, instant messaging, emails, corporate communication channels, and social media. Instead of offering do and don’t lists, however, it teaches the reader to develop a practice that is observant, reflective, and grounded in the understanding of the basic principles of language and communication. Through real-life examples and case studies, it helps the reader to notice previously unnoticed small details, question previously unchallenged assumptions and practices, and become a competent digital communicator in a wide range of professional contexts.

Relational work in synchronous text-based CMC of virtual teams

Based on close examinations of instant message (IM) interactions, this chapter argues that an interactional sociolinguistic approach to computer-mediated language use could provide explanations for phenomena that previously could not be accounted for in computer-mediated discourse analysis (CMDA). Drawing on the theoretical framework of relational work (Locher, 2006), the analysis focuses on non-task oriented talk and its function in forming and establishing communication norms in the team, as well as micro-level phenomena, such as hesitation, backchannel signals and emoticons. The conclusions of this preliminary research suggest that the linguistic strategies used for substituting audio-visual signals are strategically used in discursive functions and have an important role in relational work

Neural networks for time-varying data

This paper reviews some basic issues and methods involved in using neural networks to respond in a desired fashion to a temporally-varying environment. Some popular network models and training methods are introduced. A speech recognition example is then used to illustrate the central difficulty of temporal data processing: learning to notice and remember relevant contextual information. Feedforward network methods are applicable to cases where this problem is not severe. The application of these methods are explained and applications are discussed in the areas of pure mathematics, chemical and physical systems, and economic systems. A more powerful but less practical algorithm for temporal problems, the moving targets algorithm, is sketched and discussed. For completeness, a few remarks are made on reinforcement learning.

A novel neural network technique for exploratory data analysis

This paper surveys the context of feature extraction by neural network approaches, and compares and contrasts their behaviour as prospective data visualisation tools in a real world problem. We also introduce and discuss a hybrid approach which allows us to control the degree of discriminatory and topographic information in the extracted feature space.

Topographic mappings and feed-forward neural networks

This thesis is a study of the generation of topographic mappings - dimension reducing transformations of data that preserve some element of geometric structure - with feed-forward neural networks. As an alternative to established methods, a transformational variant of Sammon's method is proposed, where the projection is effected by a radial basis function neural network. This approach is related to the statistical field of multidimensional scaling, and from that the concept of a 'subjective metric' is defined, which permits the exploitation of additional prior knowledge concerning the data in the mapping process. This then enables the generation of more appropriate feature spaces for the purposes of enhanced visualisation or subsequent classification. A comparison with established methods for feature extraction is given for data taken from the 1992 Research Assessment Exercise for higher educational institutions in the United Kingdom. This is a difficult high-dimensional dataset, and illustrates well the benefit of the new topographic technique. A generalisation of the proposed model is considered for implementation of the classical multidimensional scaling (¸mds}) routine. This is related to Oja's principal subspace neural network, whose learning rule is shown to descend the error surface of the proposed ¸mds model. Some of the technical issues concerning the design and training of topographic neural networks are investigated. It is shown that neural network models can be less sensitive to entrapment in the sub-optimal global minima that badly affect the standard Sammon algorithm, and tend to exhibit good generalisation as a result of implicit weight decay in the training process. It is further argued that for ideal structure retention, the network transformation should be perfectly smooth for all inter-data directions in input space. Finally, there is a critique of optimisation techniques for topographic mappings, and a new training algorithm is proposed. A convergence proof is given, and the method is shown to produce lower-error mappings more rapidly than previous algorithms.

Towards sea surface pollution detection from visible band images

This paper presents a novel approach to water pollution detection from remotely sensed low-platform mounted visible band camera images. We examine the feasibility of unsupervised segmentation for slick (oily spills on the water surface) region labelling. Adaptive and non adaptive filtering is combined with density modeling of the obtained textural features. A particular effort is concentrated on the textural feature extraction from raw intensity images using filter banks and adaptive feature extraction from the obtained output coefficients. Segmentation in the extracted feature space is achieved using Gaussian mixture models (GMM).

Petrographic image analysis and understanding

This study considers the application of image analysis in petrography and investigates the possibilities for advancing existing techniques by introducing feature extraction and analysis capabilities of a higher level than those currently employed. The aim is to construct relevant, useful descriptions of crystal form and inter-crystal relations in polycrystalline igneous rock sections. Such descriptions cannot be derived until the `ownership' of boundaries between adjacent crystals has been established: this is the fundamental problem of crystal boundary assignment. An analysis of this problem establishes key image features which reveal boundary ownership; a set of explicit analysis rules is presented. A petrographic image analysis scheme based on these principles is outlined and the implementation of key components of the scheme considered. An algorithm for the extraction and symbolic representation of image structural information is developed. A new multiscale analysis algorithm which produces a hierarchical description of the linear and near-linear structure on a contour is presented in detail. Novel techniques for symmetry analysis are developed. The analyses considered contribute both to the solution of the boundary assignment problem and to the construction of geologically useful descriptions of crystal form. The analysis scheme which is developed employs grouping principles such as collinearity, parallelism, symmetry and continuity, so providing a link between this study and more general work in perceptual grouping and intermediate level computer vision. Consequently, the techniques developed in this study may be expected to find wider application beyond the petrographic domain.

Feed-forward neural networks and topographic mappings for exploratory data analysis

A recent novel approach to the visualisation and analysis of datasets, and one which is particularly applicable to those of a high dimension, is discussed in the context of real applications. A feed-forward neural network is utilised to effect a topographic, structure-preserving, dimension-reducing transformation of the data, with an additional facility to incorporate different degrees of associated subjective information. The properties of this transformation are illustrated on synthetic and real datasets, including the 1992 UK Research Assessment Exercise for funding in higher education. The method is compared and contrasted to established techniques for feature extraction, and related to topographic mappings, the Sammon projection and the statistical field of multidimensional scaling.