Co-kriging when the soil and ancillary data are not co-located

Data such as digitized aerial photographs, electrical conductivity and yield are intensive and relatively inexpensive to obtain compared with collecting soil data by sampling. If such ancillary data are co-regionalized with the soil data they should be suitable for co-kriging. The latter requires that information for both variables is co-located at several locations; this is rarely so for soil and ancillary data. To solve this problem, we have derived values for the ancillary variable at the soil sampling locations by averaging the values within a radius of 15 m, taking the nearest-neighbour value, kriging over 5 m blocks, and punctual kriging. The cross-variograms from these data with clay content and also the pseudo cross-variogram were used to co-krige to validation points and the root mean squared errors (RMSEs) were calculated. In general, the data averaged within 15m and the punctually kriged values resulted in more accurate predictions.

Use of an artificial root to examine the influence of 8-hydroxyquinoline on soil microbial activity and bacterial community structure

Invasive plant species have been shown to alter the microbial community composition of the soils they invade and it is suggested that this below-ground perturbation of potential pathogens, decomposers or symbionts may feedback positively to allow invasive success. Whether these perturbations are mediated through specific components of root exudation are not understood. We focussed on 8-hydroxyquinoline, a putative allelochemical of Centaurea diffusa (diffuse knapweed) and used an artificial root system to differentiate the effects of 8-hydroxyquinoline against a background of total rhizodeposition as mimicked through supply of a synthetic exudate solution. In soil proximal (0-10 cm) to the artificial root, synthetic exudates had a highly significant (P < 0.001) influence on dehydrogenase, fluorescein diacetate hydrolysis and urease activity. in addition, 8-hydroxyquinoline was significant (p = 0.003) as a main effect on dehydrogenase activity and interacted with synthetic exudates to affect urease activity (p = 0.09). Hierarchical cluster analysis of 16S rDNA-based DGGE band patterns also identified a primary affect of synthetic exudates and a secondary affect of 8-hydroxyquinoline on bacterial community structure. Thus, we show that the artificial rhizosphere produced by the synthetic exudates was the predominant effect, but, that the influence of the 8-hydroxyquinoline signal on the activity and structure of soil microbial communities could also be detected. (C) 2009 Elsevier Ltd. All rights reserved.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Coronary heart disease risk screening: the community pharmacy Healthy Heart Assessment Service

Objectives We examined the characteristics and CHD risks of people who accessed the free Healthy Heart Assessment (HHA) service operated by a large UK pharmacy chain from August 2004 to April 2006. Methods Associations between participants’ gender, age, and socioeconomics were explored in relation to calculated 10-year CHD risks by cross-tabulation of the data. Specific associations were tested by forming contingency tables and using Pearson chi-square (χ2). Results Data from 8,287 records were analysable; 5,377 were at low and 2,910 at moderate-to-high CHD risk. The likelihood of moderate-to-high risk for a male versus female participant was significantly higher with a relative risk ratio (RRR) 1.72 (P < 0.001). A higher percentage of those in socioeconomic categories ‘constrained by circumstances’ (RRR 1.15; P < 0.05) and ‘blue collar communities’ (RRR 1.13; P < 0.05) were assessed with moderate-to-high risk compared to those in ‘prospering suburbs’. Conclusions People from ‘hard-to-reach’ sectors of the population, men and people from less advantaged communities, accessed the HHA service and were more likely to return moderate-to-high CHD risk. Pharmacists prioritised provision of lifestyle information above the sale of a product. Our study supports the notion that pharmacies can serve as suitable environments for the delivery of similar screening services.

Stray light analysis of SALEX instrument

Discrepancies between recent global earth albedo anomaly data obtained from the climate models, space and ground observations call for a new and better earth reflectance measurement technique. The SALEX (Space Ashen Light Explorer) instrument is a space-based visible and IR instrument for precise estimation of the global earth albedo by measuring the ashen light reflected off the shadowy side of the Moon from the low earth orbit. The instrument consists of a conventional 2-mirror telescope, a pair of a 3-mirror visible imager and an IR bolometer. The performance of this unique multi-channel optical system is sensitive to the stray light contamination due to the complex optical train incorporating several reflecting and refracting elements, associated mounts and the payload mechanical enclosure. This could be further aggravated by the very bright and extended observation target (i.e. the Moon). In this paper, we report the details of extensive stray light analysis including ghosts and cross-talks, leading to the optimum set of stray light precautions for the highest signal-to-noise ratio attainable.

UK construction orders and output: A comparison of government and commercially available data 1995-2001

Because of the importance and potential usefulness of construction market statistics to firms and government, consistency between different sources of data is examined with a view to building a predictive model of construction output using construction data alone. However, a comparison of Department of Trade and Industry (DTI) and Office for National Statistics (ONS) series shows that the correlation coefcient (used as a measure of consistency) of the DTI output and DTI orders data and the correlation coefficient of the DTI output and ONS output data are low. It is not possible to derive a predictive model of DTI output based on DTI orders data alone. The question arises whether or not an alternative independent source of data may be used to predict DTI output data. Independent data produced by Emap Glenigan (EG), based on planning applications, potentially offers such a source of information. The EG data records the value of planning applications and their planned start and finish dates. However, as this data is ex ante and is not correlated with DTI output it is not possible to use this data to describe the volume of actual construction output. Nor is it possible to use the EG planning data to predict DTI construc-tion orders data. Further consideration of the issues raised reveal that it is not practically possible to develop a consistent predictive model of construction output using construction statistics gathered at different stages in the development process.

Understanding the indoor environment through mining sensory data - A case study

A wireless sensor network (WSN) is a group of sensors linked by wireless medium to perform distributed sensing tasks. WSNs have attracted a wide interest from academia and industry alike due to their diversity of applications, including home automation, smart environment, and emergency services, in various buildings. The primary goal of a WSN is to collect data sensed by sensors. These data are characteristic of being heavily noisy, exhibiting temporal and spatial correlation. In order to extract useful information from such data, as this paper will demonstrate, people need to utilise various techniques to analyse the data. Data mining is a process in which a wide spectrum of data analysis methods is used. It is applied in the paper to analyse data collected from WSNs monitoring an indoor environment in a building. A case study is given to demonstrate how data mining can be used to optimise the use of the office space in a building.

A typology of internet users based on comparative affective states: evidence from eight countries

Purpose - The role of affective states in consumer behaviour is well established. However, no study to date has empirically examined online affective states as a basis for constructing typologies of internet users and for assessing the invariance of clusters across national cultures. Design/methodology/approach - Four focus groups with internet users were carried out to adapt a set of affective states identified from the literature to the online environment. An online survey was then designed to collect data from internet users in four Western and four East Asian countries. Findings - Based on a cluster analysis, six cross-national market segments are identified and labelled "Positive Online Affectivists", "Offline Affectivists", "On/Off-line Negative Affectivists", "Online Affectivists", "Indistinguishable Affectivists", and "Negative Offline Affectivists". The resulting clusters discriminate on the basis of national culture, gender, working status and perceptions towards online brands. Practical implications - Marketers may use this typology to segment internet users in order to predict their perceptions towards online brands. Also, a standardised approach to e-marketing is not recommended on the basis of affective state-based segmentation. Originality/value - This is the first study proposing affective state-based typologies of internet users using comparable samples from four Western and four East Asian countries.

Reaping the benefits: science and the sustainable intensification of global agriculture

Food security is one of this century’s key global challenges. By 2050 the world will require increased crop production in order to feed its predicted 9 billion people. This must be done in the face of changing consumption patterns, the impacts of climate change and the growing scarcity of water and land. Crop production methods will also have to sustain the environment, preserve natural resources and support livelihoods of farmers and rural populations around the world. There is a pressing need for the ‘sustainable intensifi cation’ of global agriculture in which yields are increased without adverse environmental impact and without the cultivation of more land. Addressing the need to secure a food supply for the whole world requires an urgent international effort with a clear sense of long-term challenges and possibilities. Biological science, especially publicly funded science, must play a vital role in the sustainable intensifi cation of food crop production. The UK has a responsibility and the capacity to take a leading role in providing a range of scientifi c solutions to mitigate potential food shortages. This will require signifi cant funding of cross-disciplinary science for food security. The constraints on food crop production are well understood, but differ widely across regions. The availability of water and good soils are major limiting factors. Signifi cant losses in crop yields occur due to pests, diseases and weed competition. The effects of climate change will further exacerbate the stresses on crop plants, potentially leading to dramatic yield reductions. Maintaining and enhancing the diversity of crop genetic resources is vital to facilitate crop breeding and thereby enhance the resilience of food crop production. Addressing these constraints requires technologies and approaches that are underpinned by good science. Some of these technologies build on existing knowledge, while others are completely radical approaches, drawing on genomics and high-throughput analysis. Novel research methods have the potential to contribute to food crop production through both genetic improvement of crops and new crop and soil management practices. Genetic improvements to crops can occur through breeding or genetic modifi cation to introduce a range of desirable traits. The application of genetic methods has the potential to refi ne existing crops and provide incremental improvements. These methods also have the potential to introduce radical and highly signifi cant improvements to crops by increasing photosynthetic effi ciency, reducing the need for nitrogen or other fertilisers and unlocking some of the unrealised potential of crop genomes. The science of crop management and agricultural practice also needs to be given particular emphasis as part of a food security grand challenge. These approaches can address key constraints in existing crop varieties and can be applied widely. Current approaches to maximising production within agricultural systems are unsustainable; new methodologies that utilise all elements of the agricultural system are needed, including better soil management and enhancement and exploitation of populations of benefi cial soil microbes. Agronomy, soil science and agroecology—the relevant sciences—have been neglected in recent years. Past debates about the use of new technologies for agriculture have tended to adopt an either/or approach, emphasising the merits of particular agricultural systems or technological approaches and the downsides of others. This has been seen most obviously with respect to genetically modifi ed (GM) crops, the use of pesticides and the arguments for and against organic modes of production. These debates have failed to acknowledge that there is no technological panacea for the global challenge of sustainable and secure global food production. There will always be trade-offs and local complexities. This report considers both new crop varieties and appropriate agroecological crop and soil management practices and adopts an inclusive approach. No techniques or technologies should be ruled out. Global agriculture demands a diversity of approaches, specific to crops, localities, cultures and other circumstances. Such diversity demands that the breadth of relevant scientific enquiry is equally diverse, and that science needs to be combined with social, economic and political perspectives. In addition to supporting high-quality science, the UK needs to maintain and build its capacity to innovate, in collaboration with international and national research centres. UK scientists and agronomists have in the past played a leading role in disciplines relevant to agriculture, but training in agricultural sciences and related topics has recently suffered from a lack of policy attention and support. Agricultural extension services, connecting farmers with new innovations, have been similarly neglected in the UK and elsewhere. There is a major need to review the support for and provision of extension services, particularly in developing countries. The governance of innovation for agriculture needs to maximise opportunities for increasing production, while at the same time protecting societies, economies and the environment from negative side effects. Regulatory systems need to improve their assessment of benefits. Horizon scanning will ensure proactive consideration of technological options by governments. Assessment of benefi ts, risks and uncertainties should be seen broadly, and should include the wider impacts of new technologies and practices on economies and societies. Public and stakeholder dialogue—with NGOs, scientists and farmers in particular—needs to be a part of all governance frameworks.

(Non)differentiability and asymptotics for potential densities of subordinators

For subordinators with positive drift we extend recent results on the structure of the potential measures and the renewal densities. Applying Fourier analysis a new representation of the potential densities is derived from which we deduce asymptotic results and show how the atoms of the Lévy measure translate into points of (non)differentiability of the potential densities.

Statistical analysis of eight surface ozone measurement series for various sites in Ireland

Data from various stations having different measurement record periods between 1988 and 2007 are analyzed to investigate the surface ozone concentration, long-term trends, and seasonal changes in and around Ireland. Time series statistical analysis is performed on the monthly mean data using seasonal and trend decomposition procedures and the Box-Jenkins approach (autoregressive integrated moving average). In general, ozone concentrations in the Irish region are found to have a negative trend at all sites except at the coastal sites of Mace Head and Valentia. Data from the most polluted Dublin city site have shown a very strong negative trend of −0.33 ppb/yr with a 95% confidence limit of 0.17 ppb/yr (i.e., −0.33 ± 0.17) for the period 2002−2007, and for the site near the city of Cork, the trend is found to be −0.20 ± 0.11 ppb/yr over the same period. The negative trend for other sites is more pronounced when the data span is considered from around the year 2000 to 2007. Rural sites of Wexford and Monaghan have also shown a very strong negative trend of −0.99 ± 0.13 and −0.58 ± 0.12, respectively, for the period 2000−2007. Mace Head, a site that is representative of ozone changes in the air advected from the Atlantic to Europe in the marine planetary boundary layer, has shown a positive trend of about +0.16 ± 0.04 ppb per annum over the entire period 1988−2007, but this positive trend has reduced during recent years (e.g., in the period 2001−2007). Cluster analysis for back trajectories are performed for the stations having a long record of data, Mace Head and Lough Navar. For Mace Head, the northern and western clean air sectors have shown a similar positive trend (+0.17 ± 0.02 ppb/yr for the northern sector and +0.18 ± 0.02 ppb/yr for the western sector) for the whole period, but partial analysis for the clean western sector at Mace Head shows different trends during different time periods with a decrease in the positive trend since 1988 indicating a deceleration in the ozone trend for Atlantic air masses entering Europe.

An overview of interactive visual data mining techniques for knowledge discovery

n the past decade, the analysis of data has faced the challenge of dealing with very large and complex datasets and the real-time generation of data. Technologies to store and access these complex and large datasets are in place. However, robust and scalable analysis technologies are needed to extract meaningful information from these datasets. The research field of Information Visualization and Visual Data Analytics addresses this need. Information visualization and data mining are often used complementary to each other. Their common goal is the extraction of meaningful information from complex and possibly large data. However, though data mining focuses on the usage of silicon hardware, visualization techniques also aim to access the powerful image-processing capabilities of the human brain. This article highlights the research on data visualization and visual analytics techniques. Furthermore, we highlight existing visual analytics techniques, systems, and applications including a perspective on the field from the chemical process industry.

Can perceptual differences account for managerial success?: the case of Japanese aid workers

Purpose – There is a wealth of studies which suggest that managers' positive perceptions/expectations can considerably influence the organisational performance; unfortunately, little empirical evidence has been obtained from development studies. This research aims to focus on the perceptual and behavioural trait differences of successful and unsuccessful aid workers, and their relationship with organisational performance. Design/methodology/approach – Through web-based survey, 244 valid responses were obtained from the Japan International Cooperation Agency (JICA)-aid managers worldwide. Five perception related factors were extracted and used for cluster analysis to group the respondents. Each cluster's perception/behaviour-related factors and organisational performance variables were compared by ANOVA. Findings – It was discovered that Japanese's positive perception/expectation about work and their local colleagues was related to higher organisational performance, and conversely, the negative perception on their part was generally associated with negative behaviour and lower organisational performance. Moreover, in a development context, lower work-related stress and feelings of resignation toward work were strongly associated with the acceptability of cross-cultural work environment. Practical implications – The differences in perceptual tendencies suggest that cautious consideration is advised since these findings may mainly apply to Japanese aid managers. However, as human nature is universal, positive perception and behaviour would bring out positive output in most organisations. Originality/value – This study extended the contextualised “Pygmalion effect” and has clarified the influence of perception/expectation on counter-part behaviour and organisational performance in development aid context, where people-related issues have often been ignored. This first-time research provides imperial data on the significant role of positive perception on the incumbent role holder.

Field-perpendicular and field-aligned plasma flows observed by EISCAT during a prolonged period of northward IMF

The effect of a prolonged period of strongly northward Interplanetary Magnetic Field (IMF) on the high-latitude F-region is studied using data from the EISCAT Common Programme Zero mode of operation on 11–12 August 1982. The analysis of the raw autocorrelation functions is kept to the directly derived parameters Ne, Te, Ti and velocity, and limits are defined for the errors introduced by assumptions about ion composition and by changes in the transmitted power and system constant. Simple data-cleaning criteria are employed to eliminate problems due to coherent signals and large background noise levels. The observed variations in plasma densities, temperatures and velocities are interpreted in terms of supporting data from ISEE-3 and local riometers and magnetometers. Both field-aligned and field-perpendicular plasma flows at Tromsø showed effects of the northward IMF: convection was slow and irregular and field-aligned flow profiles were characteristic of steady-state polar wind outflow with flux of order 1012 m−2 s−1. This period followed a strongly southward IMF which had triggered a substorm. The substorm gave enhanced convection, with a swing to equatorward flow and large (5 × 1012 m−2 s−1), steady-state field-aligned fluxes, leading to the possibility of O+ escape into the magnetosphere. The apparent influence of the IMF over both field-perpendicular and field-aligned flows is explained in terms of the cross-cap potential difference and the location of the auroral oval.

Calibration and evaluation of individual-based models using Approximate Bayesian Computation

This paper investigates the feasibility of using approximate Bayesian computation (ABC) to calibrate and evaluate complex individual-based models (IBMs). As ABC evolves, various versions are emerging, but here we only explore the most accessible version, rejection-ABC. Rejection-ABC involves running models a large number of times, with parameters drawn randomly from their prior distributions, and then retaining the simulations closest to the observations. Although well-established in some fields, whether ABC will work with ecological IBMs is still uncertain. Rejection-ABC was applied to an existing 14-parameter earthworm energy budget IBM for which the available data consist of body mass growth and cocoon production in four experiments. ABC was able to narrow the posterior distributions of seven parameters, estimating credible intervals for each. ABC’s accepted values produced slightly better fits than literature values do. The accuracy of the analysis was assessed using cross-validation and coverage, currently the best available tests. Of the seven unnarrowed parameters, ABC revealed that three were correlated with other parameters, while the remaining four were found to be not estimable given the data available. It is often desirable to compare models to see whether all component modules are necessary. Here we used ABC model selection to compare the full model with a simplified version which removed the earthworm’s movement and much of the energy budget. We are able to show that inclusion of the energy budget is necessary for a good fit to the data. We show how our methodology can inform future modelling cycles, and briefly discuss how more advanced versions of ABC may be applicable to IBMs. We conclude that ABC has the potential to represent uncertainty in model structure, parameters and predictions, and to embed the often complex process of optimizing an IBM’s structure and parameters within an established statistical framework, thereby making the process more transparent and objective.