Epistemic marking and multiple perspective : an introduction

This paper discusses forms of epistemic marking that instantiate multiple perspective constructions (see Evans 2005). Such forms express the speaker’s and the addressee’s simultaneous epistemic perspectives from the point of view of the speaker, crucially relying on the assumptions of the speaker with regard to the addressee’s knowledge. The analysis of forms considers established semanto-pragmatic concepts, such as semantic scope, mitigation strategies and communicative intention (as marked by sentence-type) in the exploration of forms. In addition, the notion of knowledge asymmetry is discussed alongside the concepts of epistemic status and stance as tools for a semantic analysis of investigated forms

Statistical mechanics analysis of LDPC coding in MIMO Gaussian channels

Using analytical methods of statistical mechanics, we analyse the typical behaviour of a multiple-input multiple-output (MIMO) Gaussian channel with binary inputs under low-density parity-check (LDPC) network coding and joint decoding. The saddle point equations for the replica symmetric solution are found in particular realizations of this channel, including a small and large number of transmitters and receivers. In particular, we examine the cases of a single transmitter, a single receiver and symmetric and asymmetric interference. Both dynamical and thermodynamical transitions from the ferromagnetic solution of perfect decoding to a non-ferromagnetic solution are identified for the cases considered, marking the practical and theoretical limits of the system under the current coding scheme. Numerical results are provided, showing the typical level of improvement/deterioration achieved with respect to the single transmitter/receiver result, for the various cases. © 2007 IOP Publishing Ltd.

Political discourse analysis from the point of view of translation studies

Political discourse very often relies on translation. Political Discourse Analysis (PDA), however, has not yet taken full account of the phenomenon of translation. This paper argues that the disciplines of Translation Studies (TS) and PDA can benefit from closer cooperation. It starts by presenting examples of authentic translations of political texts, commenting on them from the point of view of TS. These examples concern political effects caused by specific translation solutions; the processes by which information is transferred via translation to another culture; and the structure and function of equally valid texts in their respective cultures. After a brief survey of the discipline of Translation Studies, the paper concludes with outlining scope for interdisciplinary cooperation between PDA and TS. This is illustrated with reference to an awareness of product features, multilingual texts, process analysis, and the politics of translation.

Multiple system atrophy (MSA): Topographic distribution of the alpha-synuclein-associated pathological changes

To study the topographic distribution of the pathology in multiple system atrophy (MSA). Pattern analysis was carried out using a-synuclein immunohistochemistry in 10 MSA cases. The glial cytoplasmic inclusions (GCI) were distributed randomly or in large clusters. The neuronal inclusions (NI) and abnormal neurons were distributed in regular clusters. Clusters of the NI and abnormal neurons were spatially correlated whereas the GCI were not spatially correlated with either the NI or the abnormal neurons. The data suggest that the GCI represent the primary change in MSA and the neuronal pathology develops secondary to the glial pathology.

A study of inputs and their influence on technological innovative activity

Technological innovation has been widely studied: however surprisingly little is known about the experience of managing the process. Most reports tend to be generalistic and/or prescriptive whereas it is argued that multiple sources of variation in the process limit the value of these. A description of the innovation process is given together with a presentation of what is knovrn from existing studies. Gaps identified in this area suggest that a variety of organisational influences are important and an attempt is made to identify some of these at individual, group and organisational level. A simple system model of the innovation management process is developed. Further investigation of the influence of these factors was made possible through an extended on-site case study. Methodology for this based upon participant observation coupled wth a wide and flexible range of techniques is described. Evidence is presented about many aspects of the innovation process from a number of different levels and perspectives: the attempt is to demonstrate the extent to which variation due to contingent influences takes place. It is argued that problems identified all relate to the issue of integration. This theme is also developed from an analytical viewoint and it is suggested that organisational response to increases in complexity in the external environment will be to match them with internal complexity. Differentiation of this kind will require extensive and flexible integration, especially in those inherently uncertain areas associated with innovation. Whilst traditionally a function of management, it is argued that integration needs have increased to the point where a new specialism is required. The concept of integration specialist is developed from this analysis and attempts at simple integrative change during the research are described. Finally a strategy for integration - or rather for building in integrative capability - ln the organisation studied is described.

Women, anger, and aggression an interpretative phenomenological analysis

This study reports a qualitative phenomenological investigation of anger and anger-related aggression in the context of the lives of individual women. Semistructured interviews with five women are analyzed using interpretative phenomenological analysis. This inductive approach aims to capture the richness and complexity of the lived experience of emotional life. In particular, it draws attention to the context-dependent and relational dimension of angry feelings and aggressive behavior. Three analytic themes are presented here: the subjective experience of anger, which includes the perceptual confusion and bodily change felt by the women when angry, crying, and the presence of multiple emotions; the forms and contexts of aggression, paying particular attention to the range of aggressive strategies used; and anger as moral judgment, in particular perceptions of injustice and unfairness. The authors conclude by examining the analytic observations in light of phenomenological thinking.

Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

Data analysis methods in optometry Part 7: multiple linear regression

Multiple regression analysis is a complex statistical method with many potential uses. It has also become one of the most abused of all statistical procedures since anyone with a data base and suitable software can carry it out. An investigator should always have a clear hypothesis in mind before carrying out such a procedure and knowledge of the limitations of each aspect of the analysis. In addition, multiple regression is probably best used in an exploratory context, identifying variables that might profitably be examined by more detailed studies. Where there are many variables potentially influencing Y, they are likely to be intercorrelated and to account for relatively small amounts of the variance. Any analysis in which R squared is less than 50% should be suspect as probably not indicating the presence of significant variables. A further problem relates to sample size. It is often stated that the number of subjects or patients must be at least 5-10 times the number of variables included in the study.5 This advice should be taken only as a rough guide but it does indicate that the variables included should be selected with great care as inclusion of an obviously unimportant variable may have a significant impact on the sample size required.

Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

A post-structural analysis of perceptions and experiences of continuity and change within the UK automotive supplier base

Firms acting as suppliers to the British automotive industry have a long history of so doing, with some evidencing histories that predate even the invention of the motor car. In exploring the challenges faced by the descendants of these firms in the 1990s, a review is undertaken of the bodies of literature surrounding the changes wrought through the increased globalisation of the industry; the impact of new manufacturing technologies and techniques; the rising levels of co-operation between firms; and the growing impact of the automotive 'service sector'. Moreover, an exploration is undertaken of the perceived 'realities' of the automotive industry as constructed through discourse, including the ways in which discourse effects a continual reinterpretation and re-evaluation of the historical evolution of the industry. Attention is focused on the implications of the above for the automotive supply chain, and the means for its rationalisation proposed by the major car manufacturers and their partner-suppliers. Post-structuralist approaches are introduced as part of an attempt to establish and appropriate research methodology that can explore and deconstruct the discourses surrounding 'modernity', 'supply chain rationalisation', 'flexible specialisation' and 'globalisation' within the automotive industry. Analytical research is conducted into the small- to medium-sized business that constitute the majority of the supplier base in the United Kingdom, and the findings of this research are compared with those of a similar study conducted a quarter-century ago. In this way, the relationships of these firms with their customers, suppliers, and peers are investigated, as are their perceptions of a changing marketplace and their reactions to the impact of policies such as the 'supply chain rationalisation' pursued by the major automotive manufacturers. Authoritative discourses of industry form, function, and structure are challenged, with voice being granted to the marginalised: small suppliers, 'service sector' firms, or those only partly involved in the automotive industry.

Multiple paradigms and organisational research: an analysis of work behaviour in the fire service

The thesis examines Kuhn's (1962, 1970) concept of paradigm, assesses how it is employed for mapping intellectual terrain in the social sciences, and evaluates it's use in research based on multiple theory positions. In so doing it rejects both the theses of total paradigm 'incommensurability' (Kuhn, 1962), and also of liberal 'translation' (Popper, 1970), in favour of a middle ground through the 'language-game of everyday life' (Wittgenstein, 1953). The thesis ultimately argues for the possibility of being 'trained-into' new paradigms, given the premise that 'unorganised experience cannot order perception' (Phillips, 1977). In conducting multiple paradigm research the analysis uses the Burrell and Morgan (1979) model for examining the work organisation of a large provincial fire Service. This analysis accounts for firstly, a 'functionalist' assessment of work design, demonstrating inter alia the decrease in reported motivation with length of service; secondly, an 'interpretive' portrayal of the daily accomplishment of task routines, highlighting the discretionary and negotiated nature of the day's events; thirdly, a 'radical humanist' analysis of workplace ideology, demonstrating the hegemonic role of officer training practices; and finally, a 'radical structuralist' description of the labour process, focusing on the establishment of a 'normal working day'. Although the argument is made for the possibility of conducting multiple paradigm research, the conclusion stresses the many institutional pressures serving to offset development.

Mathematical modelling of patient risks in a hospital environment, using multiple regression analysis

The aim of this research work was primarily to examine the relevance of patient parameters, ward structures, procedures and practices, in respect of the potential hazards of wound cross-infection and nasal colonisation with multiple resistant strains of Staphylococcus aureus, which it is thought might provide a useful indication of a patient's general susceptibility to wound infection. Information from a large cross-sectional survey involving 12,000 patients from some 41 hospitals and 375 wards was collected over a five-year period from 1967-72, and its validity checked before any subsequent analysis was carried out. Many environmental factors and procedures which had previously been thought (but never conclusively proved) to have an influence on wound infection or nasal colonisation rates, were assessed, and subsequently dismissed as not being significant, provided that the standard of the current range of practices and procedures is maintained and not allowed to deteriorate. Retrospective analysis revealed that the probability of wound infection was influenced by the patient's age, duration of pre-operative hospitalisation, sex, type of wound, presence and type of drain, number of patients in ward, and other special risk factors, whilst nasal colonisation was found to be influenced by the patient's age, total duration of hospitalisation, sex, antibiotics, proportion of occupied beds in the ward, average distance between bed centres and special risk factors. A multi-variate regression analysis technique was used to develop statistical models, consisting of variable patient and environmental factors which were found to have a significant influence on the risks pertaining to wound infection and nasal colonisation. A relationship between wound infection and nasal colonisation was then established and this led to the development of a more advanced model for predicting wound infections, taking advantage of the additional knowledge of the patient's state of nasal colonisation prior to operation.

The investigation of vegetation change using remote sensing to detect and monitor migration of landfill gas

Decomposition of domestic wastes in an anaerobic environment results in the production of landfill gas. Public concern about landfill disposal and particularly the production of landfill gas has been heightened over the past decade. This has been due in large to the increased quantities of gas being generated as a result of modern disposal techniques, and also to their increasing effect on modern urban developments. In order to avert diasters, effective means of preventing gas migration are required. This, in turn requires accurate detection and monitoring of gas in the subsurface. Point sampling techniques have many drawbacks, and accurate measurement of gas is difficult. Some of the disadvantages of these techniques could be overcome by assessing the impact of gas on biological systems. This research explores the effects of landfill gas on plants, and hence on the spectral response of vegetation canopies. Examination of the landfill gas/vegetation relationship is covered, both by review of the literature and statistical analysis of field data. The work showed that, although vegetation health was related to landfill gas, it was not possible to define a simple correlation. In the landfill environment, contribution from other variables, such as soil characteristics, frequently confused the relationship. Two sites are investigated in detail, the sites contrasting in terms of the data available, site conditions, and the degree of damage to vegetation. Gas migration at the Panshanger site was dominantly upwards, affecting crops being grown on the landfill cap. The injury was expressed as an overall decline in plant health. Discriminant analysis was used to account for the variations in plant health, and hence the differences in spectral response of the crop canopy, using a combination of soil and gas variables. Damage to both woodland and crops at the Ware site was severe, and could be easily related to the presence of gas. Air photographs, aerial video, and airborne thematic mapper data were used to identify damage to vegetation, and relate this to soil type. The utility of different sensors for this type of application is assessed, and possible improvements that could lead to more widespread use are identified. The situations in which remote sensing data could be combined with ground survey are identified. In addition, a possible methodology for integrating the two approaches is suggested.

Quantitative neuropathology:data collection and statistical analysis

The use of quantitative methods has become increasingly important in the study of neuropathology and especially in neurodegenerative disease. Disorders such as Alzheimer's disease (AD) and the frontotemporal dementias (FTD) are characterized by the formation of discrete, microscopic, pathological lesions which play an important role in pathological diagnosis. This chapter reviews the advantages and limitations of the different methods of quantifying pathological lesions in histological sections including estimates of density, frequency, coverage, and the use of semi-quantitative scores. The sampling strategies by which these quantitative measures can be obtained from histological sections, including plot or quadrat sampling, transect sampling, and point-quarter sampling, are described. In addition, data analysis methods commonly used to analysis quantitative data in neuropathology, including analysis of variance (ANOVA), polynomial curve fitting, multiple regression, classification trees, and principal components analysis (PCA), are discussed. These methods are illustrated with reference to quantitative studies of a variety of neurodegenerative disorders.