Storm prediction research and its application to the oil/gas industry

The accurate prediction of storms is vital to the oil and gas sector for the management of their operations. An overview of research exploring the prediction of storms by ensemble prediction systems is presented and its application to the oil and gas sector is discussed. The analysis method used requires larger amounts of data storage and computer processing time than other more conventional analysis methods. To overcome these difficulties eScience techniques have been utilised. These techniques potentially have applications to the oil and gas sector to help incorporate environmental data into their information systems

Construction management research: a field of application

Research in construction management is diverse in content and in quality. There is much to be learned from more fundamental disciplines. Construction is a sub-set of human experience rather than a completely separate phenomenon. Therefore, it is likely that there are few problems in construction requiring the invention of a completely new theory. If construction researchers base their work only on that of other construction researchers, our academic community will become less relevant to the world at large. The theories that we develop or test must be of wider applicability to be of any real interest. In undertaking research, researchers learn a lot about themselves. Perhaps the only difference between research and education is that if we are learning about something which no-one else knows, then it is research, otherwise it is education. Self-awareness of this will help to reduce the chances of publishing work which only reveals a researcher’s own learning curve. Scientific method is not as simplistic as non-scientists claim and is the only real way of overcoming methodological weaknesses in our work. The reporting of research may convey the false impression that it is undertaken in the sequence in which it is written. Construction is not so unique and special as to require a completely different set of methods from other fields of enquiry. Until our research is reported in mainstream journals and conferences, there is little chance that we will influence the wider academic community and a concomitant danger that it will become irrelevant. The most useful insights will come from research which challenges the current orthodoxy rather than research which merely reports it.

Construction research: a field of application

Research in construction management is diverse in content and in quality. There is much to be learned from more fundamental disciplines. Construction is a sub-set of human experience rather than a completely separate phenomenon. Therefore, it is likely that there are few problems in construction requiring the invention of a completely new theory. If construction researchers base their work only on that of other construction researchers, our academic community will become less relevant to the world at large. The theories that we develop or test must be of wider applicability to be of any real interest. In undertaking research, researchers learn a lot about themselves. Perhaps the only difference between research and education is that if we are learning about something which no-one else knows, then it is research, otherwise it is education. Self-awareness of this will help to reduce the chances of publishing work which only reveals a researcher’s own learning curve. Scientific method is not as simplistic as non-scientists claim and is the only real way of overcoming methodological weaknesses in our work. The reporting of research may convey the false impression that it is undertaken in the sequence in which it is written. Construction is not so unique and special as to require a completely different set of methods from other fields of enquiry. Until our research is reported in mainstream journals and conferences, there is little chance that we will influence the wider academic community and a concomitant danger that it will become irrelevant. The most useful insights will come from research which challenges the current orthodoxy rather than research which merely reports it.

Building synergies in development research: The application of the mosaic model to animal health research

Development research has responded to a number of charges over the past few decades. For example, when traditional research was accused of being 'top-down', the response was participatory research, linking the 'receptors' to the generators of research. As participatory processes were recognised as producing limited outcomes, the demand-led agenda was born. In response to the alleged failure of research to deliver its products, the 'joined-up' model, which links research with the private sector, has become popular. However, using examples from animal-health research, this article demonstrates that all the aforementioned approaches are seriously limited in their attempts to generate outputs to address the multi-faceted problems facing the poor. The article outlines a new approach to research: the Mosaic Model. By combining different knowledge forms, and focusing on existing gaps, the model aims to bridge basic and applied findings to enhance the efficiency and value of research, past, present, and future.

Biomarkers of the intake of dietary polyphenols: strengths, limitations and application in nutrition research

In order to establish firm evidence for the health effects of dietary polyphenol consumption, it is essential to have quantitative information regarding their dietary intake. The usefulness of the current methods, which rely mainly on the assessment of polyphenol intake using food records and food composition tables, is limited as they fail to assess total intake accurately. This review highlights the problems associated with such methods with regard to polyphenol-intake predictions. We suggest that the development of biological biomarkers, measured in both blood and urine, are essential for making accurate estimates of polyphenol intake. However, the relationship between dietary intakes and nutritional biomarkers are often highly complex. This review identifies the criteria that must be considered in the development of such biomarkers. In addition, we provide an assessment of the limited number of potential biomarkers of polyphenol intake currently available.

The utility and application of mixed-effects models in second language research

Second language acquisition researchers often face particular challenges when attempting to generalize study findings to the wider learner population. For example, language learners constitute a heterogeneous group, and it is not always clear how a study’s findings may generalize to other individuals who may differ in terms of language background and proficiency, among many other factors. In this paper, we provide an overview of how mixed-effects models can be used to help overcome these and other issues in the field of second language acquisition. We provide an overview of the benefits of mixed-effects models and a practical example of how mixed-effects analyses can be conducted. Mixed-effects models provide second language researchers with a powerful statistical tool in the analysis of a variety of different types of data.

British Nutrition Foundation annual lecture: chips with everything? Nutritional genomics and the application of diet in disease prevention

The development of high throughput techniques ('chip' technology) for measurement of gene expression and gene polymorphisms (genomics), and techniques for measuring global protein expression (proteomics) and metabolite profile (metabolomics) are revolutionising life science research, including research in human nutrition. In particular, the ability to undertake large-scale genotyping and to identify gene polymorphisms that determine risk of chronic disease (candidate genes) could enable definition of an individual's risk at an early age. However, the search for candidate genes has proven to be more complex, and their identification more elusive, than previously thought. This is largely due to the fact that much of the variability in risk results from interactions between the genome and environmental exposures. Whilst the former is now very well defined via the Human Genome Project, the latter (e.g. diet, toxins, physical activity) are poorly characterised, resulting in inability to account for their confounding effects in most large-scale candidate gene studies. The polygenic nature of most chronic diseases offers further complexity, requiring very large studies to disentangle relatively weak impacts of large numbers of potential 'risk' genes. The efficacy of diet as a preventative strategy could also be considerably increased by better information concerning gene polymorphisms that determine variability in responsiveness to specific diet and nutrient changes. Much of the limited available data are based on retrospective genotyping using stored samples from previously conducted intervention trials. Prospective studies are now needed to provide data that can be used as the basis for provision of individualised dietary advice and development of food products that optimise disease prevention. Application of the new technologies in nutrition research offers considerable potential for development of new knowledge and could greatly advance the role of diet as a preventative disease strategy in the 21st century. Given the potential economic and social benefits offered, funding for research in this area needs greater recognition, and a stronger strategic focus, than is presently the case. Application of genomics in human health offers considerable ethical and societal as well as scientific challenges. Economic determinants of health care provision are more likely to resolve such issues than scientific developments or altruistic concerns for human health.

The use of bootstrapped Malmquist indices to reassess productivity change findings: an application to a sample of Polish farms

This article assesses the extent to which sampling variation affects findings about Malmquist productivity change derived using data envelopment analysis (DEA), in the first stage by calculating productivity indices and in the second stage by investigating the farm-specific change in productivity. Confidence intervals for Malmquist indices are constructed using Simar and Wilson's (1999) bootstrapping procedure. The main contribution of this article is to account in the second stage for the information in the second stage provided by the first-stage bootstrap. The DEA SEs of the Malmquist indices given by bootstrapping are employed in an innovative heteroscedastic panel regression, using a maximum likelihood procedure. The application is to a sample of 250 Polish farms over the period 1996 to 2000. The confidence intervals' results suggest that the second half of 1990s for Polish farms was characterized not so much by productivity regress but rather by stagnation. As for the determinants of farm productivity change, we find that the integration of the DEA SEs in the second-stage regression is significant in explaining a proportion of the variance in the error term. Although our heteroscedastic regression results differ with those from the standard OLS, in terms of significance and sign, they are consistent with theory and previous research.

The dispersal of traditionally managed hay meadow plants via farmyard manure application

The dispersal of plants within botanically rich grassland is an important area of study if such swards are to be maintained. The application of farmyard manure provides a possible mechanism by which seeds contained within hay can be returned/introduced to grasslands. In this study, hay, dung and manure samples taken from farms with botanically rich meadows contained very limited quantities of seeds of desirable species. Digestion by cattle, and storage within a manure heap for 6 months or longer, further reduced seed germination. Samples were characterized by an abundance of the grass, Poa trivialis, with few forbs present. Confirmation of the negative effect of the digestive processes of cattle on seed viability was achieved using an in vitro laboratory experiment. However, this experiment did show that the perennial herbs, Filipendula ulmaria and Sanguisorba officinalis, were able to survive digestion at least as well as P. trivialis. The burial of known quantities of seeds in a manure heap also showed these perennial herbs to be at least as resistant to damage as P. trivialis. The results demonstrate that, given appropriate timing of the hay cut, seeds of species with high conservation value could become incorporated into manure for subsequent dispersal. However, manure dispersal would appear to be of limited value for many species desirable from a conservation viewpoint.

International public goods through integrated natural resources management research in CGIAR partnerships

The CGIAR System conducts research to produce international public goods (IPG) that are of wide applicability creating a scientific base which speeds and broadens local adaptive development. Integrated natural resources management (INRM) research is sometimes seen to be very location specific and consequently does not lend itself readily to the production of IPGs. In this paper we analyse ways in which strategic approaches to INRM research can have broad international applicability and serve as useful foundations for the development of locally adapted technologies. The paper describes the evolution of the IPG concept within the CGIAR and elaborates on five major types of IPGs that have been generated from a varied set of recent INRM research efforts. CGIAR networks have both strengths and weaknesses in INRM research and application, with enormous differences in relative research and development capacities, responsibilities and data access of its partners, making programme process evolution critical to acceptance and participation. Many of the lessons learnt regarding challenges and corresponding IPG research approaches are relevant to designing and managing future multi-scale, multi-locational, coordinated INRM programmes involving broad-based partnerships to address complex environmental and livelihood problems for development.

Typification of farming systems for constructing representative farm models: two illustrations of the application of multi-variate analyses in Chile and Pakistan

If the fundamental precepts of Farming Systems Research were to be taken literally then it would imply that for each farm 'unique' solutions should be sought. This is an unrealistic expectation, but it has led to the idea of a recommendation domain, implying creating a taxonomy of farms, in order to increase the general applicability of recommendations. Mathematical programming models are an established means of generating recommended solutions, but for such models to be effective they have to be constructed for 'truly' typical or representative situations. The multi-variate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available. This paper illustrates the application of this methodology in two different studies that shared the common purpose of identifying types of farming systems in their respective study areas. The issues related with the use of factor and cluster analyses for farm typification prior to building representative mathematical programming models for Chile and Pakistan are highlighted. (C) 2003 Elsevier Science Ltd. All rights reserved.