The effects of public funding on farmers' attitudes to farm diversification

The overall aim of this research is to provide the UK Government with an evidence base from which it may be established whether there is a rationale for continuing Government intervention to encourage farm diversification, in particular through making capital grant funding available to farm diversification projects. The project's findings will inform the future role of government support, including whether other forms of support (advice, guidance and training) may be appropriate.Agricultural and Food Policy, Agricultural Finance, Farm Management,

The Wider Social Impacts of Changes in the Structure of Agricultural Businesses

Agricultural restructuring is not a new phenomenon. Indeed, recent decades have seen substantial changes, not only to the number and types of farmers and farm businesses, but also to ownership structures and to the relationship between land holding and management control. The Department of Food, Environment and Rural Affairs (Defra), together with the UK Countryside Agencies, has commissioned a body of research in recent years which, taken together, offer important insights into the nature, speed and extent of restructuring in the UK and of the potential for further, accelerated change in the years to come. From this body of work it is clear that a prolonged and difficult process of disengagement from agriculture as a mainstream income source is beginning to take place, with evidence of both adaptation and resistance to change by a land management community which is becoming increasingly diverse in its social composition and behaviour. The adjustment to farming practice, living standards and lifestyles which all of this implies is not without personal cost and, while claims of an agricultural crisis may be exaggerated, it is clear that large numbers of farmers are finding they have to make difficult adjustments against a shifting background of policy reform and market change. Moreover, given the traditional centrality of farmers in rural communities, both as employers and as participants in many of the key institutions of rural life, there may be wider social implications of agricultural restructuring which now deserve to be more closely investigated. What, for example is the nature, extent and wider significance of the personal costs and social implications of agricultural restructuring.Agribusiness, Industrial Organization,

Blurring the boundaries of the Mackintosh room

In this paper we describe a prototype interactive systemsupporting a shared synchronous experience for physical,World Wide Web and virtual reality visitors to anexhibition devoted to the designer and architect C.R.Mackintosh. The system provides awareness betweenvisitors that spans multiple media while also providinglocation- and device-sensitive content to each visitor

The wider social impacts of changes in the structure of agricultural businesses

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Estimating cropland requirements for global food system scenario modeling

IntroductionThe production of plant crops is foundational to the global food system. With the need for this system to become more sustainable while feeding an increasing global population, tools to investigate future food system scenarios can be useful to aid decision making, but are often limited to a calorie- or protein-centric view of human nutrition.MethodsHere, a mathematical model for forecasting the future cropland requirement to produce a given quantity of crop mass is presented in conjunction with the DELTA Model®: an existing food system scenario model calculating global availability of 29 nutrients against human requirements. The model uses national crop yield data to assign yield metrics for 137 crops.ResultsThe crops with the greatest variation between high and low yielding production were specific nuts, fruits, and vegetables of minor significance to global nutrient availability. The nut crop group showed the greatest overall yield variation between countries, and thus the greatest uncertainty when forecasting the cropland requirement for future increases in production. Sugar crops showed the least overall yield variation. The greatest potential for increasing global food production by improving poor yielding production was found for the most widely grown crops: maize, wheat, and rice, which were also demonstrated to be of high nutritional significance.DiscussionThe combined cropland and nutrient availability model allowed the contribution of plant production to global nutrition to be quantified, and the cropland requirement of future food production scenarios to be estimated. The unified cropland estimation and nutrient availability model presented here is an intuitive and broadly applicable tool for use in global food system scenario modeling. It should benefit future research and policy making by demonstrating the implications for human nutrition of changes to crop production, and conversely the implications for cropland requirement of food production scenarios aimed at improving nutrition

A nanobody-based tracer targeting DPP6 for non-invasive imaging of human pancreatic endocrine cells

There are presently no reliable ways to quantify endocrine cell mass (ECM) in vivo, which prevents an accurate understanding of the progressive beta cell loss in diabetes or following islet transplantation. To address this unmet need, we coupled RNA sequencing of human pancreatic islets to a systems biology approach to identify new biomarkers of the endocrine pancreas. Dipeptidyl-Peptidase 6 (DPP6) was identified as a target whose mRNA expression is at least 25-fold higher in human pancreatic islets as compared to surrounding tissues and is not changed by proinflammatory cytokines. At the protein level, DPP6 localizes only in beta and alpha cells within the pancreas. We next generated a high-affinity camelid single-domain antibody (nanobody) targeting human DPP6. The nanobody was radiolabelled and in vivo SPECT/CT imaging and biodistribution studies were performed in immunodeficient mice that were either transplanted with DPP6-expressing Kelly neuroblastoma cells or insulin-producing human EndoC-βH1 cells. The human DPP6-expressing cells were clearly visualized in both models. In conclusion, we have identified a novel beta and alpha cell biomarker and developed a tracer for in vivo imaging of human insulin secreting cells. This provides a useful tool to non-invasively follow up intramuscularly implanted insulin secreting cells

Undergraduate Research Participation in Electrical Engineering

During the 1990-2003 summers the Electrical Engineering Department at the University of Maine will offer ten undergraduate students the opportunity to actively participate in research. Students will receive financial awards plus a subsistence allowance. The available research projects include (1) Environmental Sensors; (2) Intelligent Systems for Automation; (3) Communications Devices and Applications; (4) Motion Control; (5) Microprocessor/Instrumentation Applications; (6) Growth and Characterization of Thin Film Materials; and (7) Power Systems Applications. At least five students will come from institutions where research opportunities are limited and at least four students will be women, minorities or students with disabilities. Students chosen for the program will have displayed a high degree of initiative and independence of thought in both laboratories and course work. Student research projects are chosen to match the student\u27s interest and educational level. In addition to extensive University facilities, students will also have access to facilities at various nearby industries such as Sensor Research and Development Corporation, BIODE Corporation, Bangor Hydro Electric and Central Maine Power Companies, James River, Champion, and Scott Paper Companies, Digital Equipment Corporation, Fairchild and National Semiconductor. At the program culmination a written report and an oral seminar are required from the student. Three academic credits are awarded to the student upon satisfactory completion of the program

Can a systems approach produce a better understanding of mood disorders?

Background: One in twenty-five people suffer from a mood disorder. Current treatments are sub-optimal with poor patient response and uncertain modes-of-action. There is thus a need to better understand underlying mechanisms that determine mood, and how these go wrong in affective disorders. Systems biology approaches have yielded important biological discoveries for other complex diseases such as cancer, and their potential in affective disorders will be reviewed. Scope of review: This review will provide a general background to affective disorders, plus an outline of experimental and computational systems biology. The current application of these approaches in understanding affective disorders will be considered, and future recommendations made. Major conclusions: Experimental systems biology has been applied to the study of affective disorders, especially at the genome and transcriptomic levels. However, data generation has been slowed by a lack of human tissue or suitable animal models. At present, computational systems biology has only be applied to understanding affective disorders on a few occasions. These studies provide sufficient novel biological insight to motivate further use of computational biology in this field. General significance: In common with many complex diseases much time and money has been spent on the generation of large-scale experimental datasets. The next step is to use the emerging computational approaches, predominantly developed in the field of oncology, to leverage the most biological insight from these datasets. This will lead to the critical breakthroughs required for more effective diagnosis, stratification and treatment of affective disorders