Lost in semantic space: a multi-modal, non-verbal assessment of feature knowledge in semantic dementia

A novel, non-verbal test of semantic feature knowledge is introduced, enabling subordinate knowledge of four important concept attributes--colour, sound, environmental context and motion--to be individually probed. This methodology provides more specific information than existing non-verbal semantic tests about the status of attribute knowledge relating to individual concept representations. Performance on this test of a group of 12 patients with semantic dementia (10 male, mean age: 64.4 years) correlated strongly with their scores on more conventional tests of semantic memory, such as naming and word-to-picture matching. The test's overlapping structure, in which individual concepts were probed in two, three or all four modalities, provided evidence of performance consistency on individual items between feature conditions. Group and individual analyses revealed little evidence for differential performance across the four feature conditions, though sound and colour correlated most strongly, and motion least strongly, with other semantic tasks, and patients were less accurate on the motion features of living than non-living concepts (with no such conceptual domain differences in the other conditions). The results are discussed in the context of their implications for the place of semantic dementia within the classification of progressive aphasic syndromes, and for contemporary models of semantic representation and organization

Category-specific deficits: Insights from semantic dementia and Alzheimer's disease

Recent investigations and theorising about category-specific deficits have begun to focus upon patients with progressive brain disease such as semantic dementia and Alzheimer's disease. In this commentary we briefly review what insights have been gained from studying patients of this type. We concentrate on four specific issues: the sensory/functional distinction, correlation between features, neuroanatomical considerations, and confounding factors

Semantic memory is impaired in both dementia with Lewy Bodies (DLB) and dementia of Alzheimer's type (DAT): a comparative neuropsychological study and literature review

OBJECTIVE---To test the hypothesis that semantic impairment is present in both patients with dementia with Lewy bodies (DLB) and those with dementia of Alzheimer's type (DAT). METHODS---A comprehensive battery of neuropsychological tasks designed to assess semantic memory, visuoperceptual function, verbal fluency, and recognition memory was given to groups of patients with DLB (n=10), DAT (n=10) matched pairwise for age and mini mental state examination (MMSE), and age matched normal controls (n=15). RESULTS---Both DLB and DAT groups exhibited impaired performance across the range of tasks designed to assess semantic memory. Whereas patients with DAT showed equivalent comprehension of written words and picture stimuli, patients with DLB demonstrated more severe semantic deficits for pictures than words. As in previous studies, patients with DLB but not those with DAT were found to have impaired visuoperceptual functioning. Letter and category fluency were equally reduced for the patients with DLB whereas performance on letter fluency was significantly better in the DAT group. Recognition memory for faces and words was impaired in both groups. CONCLUSIONS---Semantic impairment is not limited to patients with DAT. Patients with DLB exhibit particular problems when required to access meaning from pictures that is most likely to arise from a combination of semantic and visuoperceptual impairments

Active flutter control for flexible vehicles, volume 1

An active flutter control methodology based on linear quadratic gaussian theory and its application to the control of a super critical wing is presented. Results of control surface and sensor position optimization are discussed. Both frequency response matching and residualization used to obtain practical flutter controllers are examined. The development of algorithms and computer programs for flutter modeling and active control design procedures is reported

Avoiding the archetype: reading and writing the female artist

This exegesis takes Margaret Atwood’s Cat’s Eye (1988) and Jessica Anderson’s Tirra Lirra by the River (1978) as case studies within a critique of the structuralist view of the male artist’s novel (kunstlerroman ) and more recent structuralist readings of the female artist’s novel (kunstlerinroman ). It discusses Maurice Beebe’s and Linda Huf’s critical writings about fictional artist-portrayals and investigates the ways in which the post-modernist and feminist case studies conform with and challenge these theories. It argues that, by stereotyping the personality and largely the experience of the artist, the possibilities for individualized motive and character, as well as the opportunity for deeper interpretation of the text, are denied. As Roland Barthes famously asserts: ‘To give a text an Author is to impose limits on that text, to furnish it with a final signified, to close the writing.’ In examining the two case studies, this exegesis aims to dispel the myth that there can be one archetypal artist story. Through discussions relating to identity, gender and structure, this exegesis reveals that Cat’s Eye and Tirra Lirra borrow from tradition before ‘decentering’ the genre. This is achieved through a circular treatment of time and a multi-layered thematic landscape presented through the prism of memory and identity. Where structuralist theory presents the artist protagonist as striving to conform to an image predetermined by cultural notions and literary conventions, my case studies insist that, above the artworks produced by the protagonists, the reinterpretation and retelling of their own life stories is a creative triumph for each

The role of working memory and verbal fluency in autobiographical memory in early Alzheimer’s disease and matched controls

Retrieval of autobiographical memories (AMs) is important for “sense of self”. Previous research and theoretical accounts suggest that working memory (WM) and semantic and phonemic fluency abilities facilitate the hierarchical search for, and reliving of past, personal events in the mind’s eye. However, there remains a lack of consensus as to the nature of the relationships between these cognitive functions and the truly episodic aspects of AM. The present study therefore aimed to explore the associations between these variables in a sample with a wide range of cognitive abilities. The study incorporated a between-groups component, and a correlational component with multiple regression. Participants with Alzheimer’s disease (n = 10) and matched healthy controls (n = 10) were assessed on measures of semantic and episodic AM search and retrieval, auditory and spatial WM, and semantic and phonemic fluency. The AD group produced less episodic AM content compared to controls. Semantic fluency predicted episodic AM retrieval independent of age effects but there were no significant relationships between measures of phonemic fluency, WM and episodic AM. The results suggest that the ability to maintain hierarchical search of the semantic knowledge-base is important for truly episodic reliving, and interventions for people with AM impairment might therefore benefit from incorporating structured, individualised external memory-aids to facilitate AM search and retrieval

Integrating methods for ecosystem service assessment and valuation: mixed methods or mixed messages?

A mixed-method approach was used to assess and value the ecosystem services derived from the Dogger Bank, an extensive shallow sandbank in the southern North Sea. Three parallel studies were undertaken that 1) identified and quantified, where possible, how indicators for ecosystem service provision may change according to two future scenarios, 2) assessed members of the public's willingness-to-pay for improvements to a small number of ecosystem services as a consequence of a hypothetical management plan, and 3) facilitated a process of deliberation that allowed members of the public to explore the uses of the Dogger Bank and the conflicts and dilemmas involved in its management. Each of these studies was designed to answer different and specific research questions and therefore contributes different insights about the ecosystem services delivered by the Dogger Bank. This paper explores what can be gained by bringing these findings together post hoc and the extent to which the different methods are complementary. Findings suggest that mixed-method research brings more understanding than can be gained from the individual approaches alone. Nevertheless, the choice of methods used and how these methods are implemented strongly affects the results obtained

Nonlinear Dynamic Modeling and Controls Development for Supersonic Propulsion System Research

This paper covers the propulsion system component modeling and controls development of an integrated nonlinear dynamic simulation for an inlet and engine that can be used for an overall vehicle (APSE) model. The focus here is on developing a methodology for the propulsion model integration, which allows for controls design that prevents inlet instabilities and minimizes the thrust oscillation experienced by the vehicle. Limiting thrust oscillations will be critical to avoid exciting vehicle aeroelastic modes. Model development includes both inlet normal shock position control and engine rotor speed control for a potential supersonic commercial transport. A loop shaping control design process is used that has previously been developed for the engine and verified on linear models, while a simpler approach is used for the inlet control design. Verification of the modeling approach is conducted by simulating a two-dimensional bifurcated inlet and a representative J-85 jet engine previously used in a NASA supersonics project. Preliminary results are presented for the current supersonics project concept variable cycle turbofan engine design

Absolute Calibration of the Auger Fluorescence Detectors

Absolute calibration of the Pierre Auger Observatory fluorescence detectors uses a light source at the telescope aperture. The technique accounts for the ombined effects of all detector components in a single measurement. The calibrated 2.5 m diameter light source fills the aperture, providing uniform illumination to each pixel. The known flux from the light source and the response of the acquisition system give the required calibration for each pixel. In the lab, light source uniformity is studied using CCD images and the intensity is measured relative to NIST-calibrated photodiodes. Overall uncertainties are presently 12%, and are dominated by systematics.Comment: 4 pages, 3 figure. Submitted to the 29th ICRC, Pune, Indi

How to do things with (thousands of) words: Computational approaches to discourse analysis in Alzheimer's disease.

Natural Language Processing (NLP) is an ever-growing field of computational science that aims to model natural human language. Combined with advances in machine learning, which learns patterns in data, it offers practical capabilities including automated language analysis. These approaches have garnered interest from clinical researchers seeking to understand the breakdown of language due to pathological changes in the brain, offering fast, replicable and objective methods. The study of Alzheimer's disease (AD), and preclinical Mild Cognitive Impairment (MCI), suggests that changes in discourse (connected speech or writing) may be key to early detection of disease. There is currently no disease-modifying treatment for AD, the leading cause of dementia in people over the age of 65, but detection of those at risk of developing the disease could help with the identification and testing of medications which can take effect before the underlying pathology has irreversibly spread. We outline important components of natural language, as well as NLP tools and approaches with which they can be extracted, analysed and used for disease identification and risk prediction. We review literature using these tools to model discourse across the spectrum of AD, including the contribution of machine learning approaches and Automatic Speech Recognition (ASR). We conclude that NLP and machine learning techniques are starting to greatly enhance research in the field, with measurable and quantifiable language components showing promise for early detection of disease, but there remain research and practical challenges for clinical implementation of these approaches. Challenges discussed include the availability of large and diverse datasets, ethics of data collection and sharing, diagnostic specificity and clinical acceptability