Carbon reduction in buildings (CaRB) - Understanding the social and technical factors that influence energy use in UK buildings

Attempts to reduce the energy consumed in UK homes have met with limited success. One reason for this is a lack of understanding of how people interact with domestic technology – heating systems, lights, electrical equipment and so forth. Attaining such an understanding is hampered by a chronic shortage of detailed energy use data matched to descriptions of the house, the occupants, the internal conditions and the installed services and appliances. Without such information it is impossible to produce transparent and valid models for understanding and predicting energy use. The Carbon Reduction in Buildings (CaRB) consortium of five UK universities plans to develop socio-technical models of energy use, underpinned by a flow of data from a longitudinal monitoring campaign involving several hundred UK homes. This paper outlines the models proposed, the preliminary monitoring work and the structure of the proposed longitudinal study.

Learning across business sectors: facets of innovation in aerospace and construction

Innovation is notoriously difficult to define and is invariably intertwined with issues of knowledge creation, continuous improvement and organisational change. An extensive literature classifies numerous types of innovation and militates against any simplistic attempt at definition. It is widely accepted that innovation is at least partly dependent upon the surrounding environment. Industry recipes and institutionally embedded practices shape the environment within which innovation occurs. Recent research directions have addressed the diffusion of innovation and its dependence upon social and institutional structures. In this respect, it is highly pertinent to compare the way that innovation is interpreted and enacted in different industrial sectors. The comparison between UK aerospace and construction is especially revealing because the two sectors are so different and therefore constitute radically different climates for innovation. Empirical research is reported based on semi-structured interviews with practitioners from both sectors. Interpretations of innovation are found to differ dramatically between aerospace and construction. Within the context of an ongoing struggle to define innovation, both industries are striving to become more innovative. The aerospace sector is found to emphasise technical innovation whereas the construction sector emphasises process innovation. An overriding cultural bias in Western economies towards technological innovation results in the common perception that aerospace is much more innovative than construction. The experienced realities of practitioners in the two sectors are much more complex.

Cognitive behaviour therapy for psychosis: current evidence and future directions

The past decade has seen considerable growth in the evidence base of cognitive behavioural therapy for psychosis. Consistent reports of moderate effect sizes have led to such interventions being recommended as part of routine clinical practice. Most of this evidence is based on a generic form of CBT for psychosis applied to a heterogeneous group. An increase in the effectiveness of cognitive behavioural interventions may require new protocols. Such therapeutic developments should be based on the theoretical understanding of the psychological processes associated with specific forms of psychotic presentation. The current evidence base of CBT for psychosis is reviewed, and barriers that have held back the development of this research are discussed.

Future directions for doll play narrative research: a commentary

Past research into doll play narratives has been productive in elucidating children's inner experiences, their determinants, and their role in child behaviour problems. The current volume takes this work forward in several directions: first, it indicates the value of designing story stems and coding schemes to address more specific questions about the developmental process of specific syndromes. Second, contributions demonstrate the "added value" provided by children's narratives, over and above information derived from other sources. Third, this recent research enhances our understanding of the role of parental representations and states of mind in influencing children's narratives; how these may come to influence child functioning via co-constructed parent-child dialogues is an important area for future research. Finally, possibilities of extending the clinical utility of doll play narratives are explored.

Cognitive therapy for anxiety disorders: current status and future directions.

This paper reviews recent theoretical, conceptual and practice developments in cognitive-behaviour therapy (CBT) for anxiety disorders. The empirical status of CBT for anxiety disorders is reviewed and recent advances in the field are outlined. Challenges for the future development of CBT for the anxiety disorders are examined in relation to the efficacy, effectiveness and cost-effectiveness of the approach. It is concluded that the major challenge currently facing CBT for anxiety disorders in the UK is how to meet the increased demand for provision whilst maintaining high levels of efficacy and effectiveness. It is suggested that the creation of an evidence base for the dissemination of CBT needs to become a priority for empirical investigation in order effectively to expand the provision of CBT for anxiety disorders.

Future directions for child anxiety theory and treatment

The aim of this introductory paper, and of this special issue of Cognition and Emotion, is to stimulate debate about theoretical issues that will inform child anxiety research in the coming years. Papers included in this special issue have arisen from an Economic and Social Research Council (ESRC, UK) funded seminar series, which we called Child Anxiety Theory and Treatment (CATTS). We begin with an overview of the CATTS project before discussing (1) the application of adult models of anxiety to children, and (2) the role of parents in child anxiety. We explore the utility of adult models of anxiety for child populations before discussing the problems that are associated with employing them uncritically in this context. The study of anxiety in children provides the opportunity to observe the trajectory of anxiety and to identify variables that causally influence its development. Parental influences are of particular interest and new and imaginative strategies are required to isolate the complex network of causal relationships therein. We conclude by suggesting that research into the causes and developmental course of anxiety in children should be developed further. We also propose that, although much is known about the role of parents in the development of anxiety, it would be useful for research in this area to move towards an examination of the specific processes involved. We hope that these views represent a constructive agenda for people in the field to consider when planning future research.

Family treatment of child anxiety: outcomes, limitations and future directions

Anxiety of childhood is a common and serious condition. The past decade has seen an increase in treatment-focussed research, with recent trials tending to give greater attention to parents in the treatment process. This review examines the efficacy of family-based cognitive behaviour therapy and attempts to delineate some of the factors that might have an impact on its efficacy. The choice and timing of outcome measure, age and gender of the child, level of parental anxiety, severity and type of child anxiety and treatment format and content are scrutinised. The main conclusions are necessarily tentative, but it seems likely that Family Cognitive Behaviour Therapy (FCBT) is superior to no treatment, and, for some outcome measures, also superior to Child Cognitive Behaviour Therapy (CCBT). Where FCBT is successful, the results are consistently maintained at follow-up. It appears that where a parent is anxious, and this is not addressed, outcomes are less good. However, for children of anxious parents, FCBT is probably more effective than CCBT. What is most clear is that large, well-designed studies, examining these factors alone and in combination, are now needed.

Actors and objects: A socio-technical networks approach for construction management research

We explore the contribution of socio-technical networks approaches to construction management research. These approaches are distinctive for their analysis of actors and objects as mutually constituted within socio-technical networks. They raise questions about the ways in which the content, meaning and use of technology is negotiated in practice, how particular technical configurations are elaborated in response to specific problems and why certain paths or solutions are adopted rather than others. We illustrate this general approach with three case studies: a historical study of the development of reinforced concrete in France, the UK and the US, the recent introduction of 3D-CAD software into four firms and an analysis of the uptake of environmental assessment technologies in the UK since 1990. In each we draw out the ways in which various technologies shaped and were shaped by different socio-technical networks. We conclude with a reflection on the contributions of socio-technical network analysis for more general issues including the study of innovation and analyses of context and power.

Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).