The environmental impacts of technical change

The thesis is concerned with relationships between profit, technology and environmental change. Existing work has concentrated on only a few questions, treated at either micro or macro levels of analysis. And there has been something of an impasse since the neoclassical and neomarxist approaches are either in direct conflict (macro level), or hardly interact (micro level). The aim of the thesis was to bypass this impasse by starting to develop a meso level of analysis that focusses on issues largely ignored in the traditional approaches - on questions about distribution. The first questions looked at were descriptive - what were the patterns of distribution over time of the variability in types and rates of environmental change, and in particular, was there any evidence of periodization? Two case studies were used to examine these issues. The first looked at environmental change in the iron and steel industry since 1700, and the second studied pollution in five industries in the basic processing sector. It was established that environmental change has been markedly periodized, with an apparently fairly regular `cycle length' of about fifty years. The second questions considered were explanatory - whether and how this periodization could be accounted for by reference to variations in aspects of profitability and technical change. In the iron and steel industry, it was found that diffusion rates and the rate of nature of innovation were periodized on the same pattern as was environmental change. And the same sort of variation was also present in the realm of profits, as evidenced by cyclical changes in output growth. Simple theoretical accounts could be given for all the empirically demonstrable links, and it was suggested that the most useful models at this meso level of analysis are provided by structural change models of economic development.

Progressive structural analysis for dynamic recognition of on-line handwritten mathematical expressions

Structural analysis in handwritten mathematical expressions focuses on interpreting the recognized symbols using geometrical information such as relative sizes and positions of the symbols. Most existing approaches rely on hand-crafted grammar rules to identify semantic relationships among the recognized mathematical symbols. They could easily fail when writing errors occurred. Moreover, they assume the availability of the whole mathematical expression before being able to analyze the semantic information of the expression. To tackle these problems, we propose a progressive structural analysis (PSA) approach for dynamic recognition of handwritten mathematical expressions. The proposed PSA approach is able to provide analysis result immediately after each written input symbol. This has an advantage that users are able to detect any recognition errors immediately and correct only the mis-recognized symbols rather than the whole expression. Experiments conducted on 57 most commonly used mathematical expressions have shown that the PSA approach is able to achieve very good performance results.

Innate recognition of apoptotic cells:novel apoptotic cell-associated molecular patterns revealed by crossreactivity of anti-LPS antibodies

Cells dying by apoptosis are normally cleared by phagocytes through mechanisms that can suppress inflammation and immunity. Molecules of the innate immune system, the pattern recognition receptors (PRRs), are able to interact not only with conserved structures on microbes (pathogen-associated molecular patterns, PAMPs) but also with ligands displayed by apoptotic cells. We reasoned that PRRs might therefore interact with structures on apoptotic cells-apoptotic cell-associated molecular patterns (ACAMPs)-that are analogous to PAMPs. Here we show that certain monoclonal antibodies raised against the prototypic PAMP, lipopolysaccharide (LPS), can crossreact with apoptotic cells. We demonstrate that one such antibody interacts with a constitutively expressed intracellular protein, laminin-binding protein, which translocates to the cell surface during apoptosis and can interact with cells expressing the prototypic PRR, mCD14 as well as with CD14-negative cells. Anti-LPS cross reactive epitopes on apoptotic cells colocalised with annexin V-and C1q-binding sites on vesicular regions of apoptotic cell surfaces and were released associated with apoptotic cell-derived microvesicles (MVs). These results confirm that apoptotic cells and microbes can interact with the immune system through common elements and suggest that anti-PAMP antibodies could be used strategically to characterise novel ACAMPs associated not only with apoptotic cells but also with derived MVs. © 2013 Macmillan Publishers Limited All rights reserved.

Examination of the predictive value of structural magnetic resonance scans in bipolar disorder:a pattern classification approach

Background - Bipolar disorder (BD) is one of the leading causes of disability worldwide. Patients are further disadvantaged by delays in accurate diagnosis ranging between 5 and 10 years. We applied Gaussian process classifiers (GPCs) to structural magnetic resonance imaging (sMRI) data to evaluate the feasibility of using pattern recognition techniques for the diagnostic classification of patients with BD. Method - GPCs were applied to gray (GM) and white matter (WM) sMRI data derived from two independent samples of patients with BD (cohort 1: n = 26; cohort 2: n = 14). Within each cohort patients were matched on age, sex and IQ to an equal number of healthy controls. Results - The diagnostic accuracy of the GPC for GM was 73% in cohort 1 and 72% in cohort 2; the sensitivity and specificity of the GM classification were respectively 69% and 77% in cohort 1 and 64% and 99% in cohort 2. The diagnostic accuracy of the GPC for WM was 69% in cohort 1 and 78% in cohort 2; the sensitivity and specificity of the WM classification were both 69% in cohort 1 and 71% and 86% respectively in cohort 2. In both samples, GM and WM clusters discriminating between patients and controls were localized within cortical and subcortical structures implicated in BD. Conclusions - Our results demonstrate the predictive value of neuroanatomical data in discriminating patients with BD from healthy individuals. The overlap between discriminative networks and regions implicated in the pathophysiology of BD supports the biological plausibility of the classifiers.

Design and designing:a critical introduction

Design and Designing provides a broad and critical understanding of what is essentially a practical subject. Designing today is less a craft and more a part of the knowledge economy. It's all about knowing how to acquire knowledge and how to apply it creatively. Design and Designing covers the design process, modelling and drawing, working with clients, production and consumption, sustainability, professional practice and design futures. Chapters are written by expert teachers and practitioners from around the globe, each presenting an accessible and engaging overview of their field of design. Every chapter is highly illustrated with a combination of images and information boxes, which extend or highlight key material. Each section concludes with a design project, a hands-on activity for the reader. Design and Designing covers the full spectrum of design types, from graphic communication to product design, from fashion to games design, setting every type in its aesthetic, ethical and social contexts. With this essential book, readers will learn from today's best practice and best thinking in design, they will develop a critical sense, and become the designers of tomorrow.

The impact of context on pattern category learning and representation

Context traditionally has been regarded in vision research as a determinant for the interpretation of sensory information on the basis of previously acquired knowledge. Here we propose a novel, complementary perspective by showing that context also specifically affects visual category learning. In two experiments involving sets of Compound Gabor patterns we explored how context, as given by the stimulus set to be learned, affects the internal representation of pattern categories. In Experiment 1, we changed the (local) context of the individual signal classes by changing the configuration of the learning set. In Experiment 2, we varied the (global) context of a fixed class configuration by changing the degree of signal accentuation. Generalization performance was assessed in terms of the ability to recognize contrast-inverted versions of the learning patterns. Both contextual variations yielded distinct effects on learning and generalization thus indicating a change in internal category representation. Computer simulations suggest that the latter is related to changes in the set of attributes underlying the production rules of the categories. The implications of these findings for phenomena of contrast (in)variance in visual perception are discussed.