Determination of the impact of continuous defoliation of Lolium perenne and Trifolium repens on bacterial and fungal community structure in rhizosphere soil

To determine the effects of defoliation on microbial community structure, rhizosphere soil samples were taken pre-, and post-defoliation from the root tip and mature root regions of Trifolium repens L. and Lolium perenne L. Microbial DNA isolated from samples was used to generate polymerase chain reaction-denaturing gradient gel electrophoresis molecular profiles of bacterial and fungal communities. Bacterial plate counts were also obtained. Neither plant species nor defoliation affected the bacterial and fungal community structures in both the root tip and mature root regions, but there were significant differences in the bacterial and fungal community profiles between the two root regions for each plant. Prior to defoliation, there was no difference between plants for bacterial plate counts of soils from the root tip regions; however, counts were greater in the mature root region of L. perenne than T. repens. Bacterial plate counts for T. repens were higher in the root tip than the mature root region. After defoliation, there was no effect of plant type, position along the root or defoliation status on bacterial plate counts, although there were significant increases in bacterial plate counts with time. The results indicate that a general effect existed during maturation in the root regions of each plant, which had a greater impact on microbial community structure than either plant type or the effect of defoliation. In addition there were no generic consequences with regard to microbial populations in the rhizosphere as a response to plant defoliation.

Assessing the uncertainty associated with intermittent rainfall fields

[1] In many practical situations where spatial rainfall estimates are needed, rainfall occurs as a spatially intermittent phenomenon. An efficient geostatistical method for rainfall estimation in the case of intermittency has previously been published and comprises the estimation of two independent components: a binary random function for modeling the intermittency and a continuous random function that models the rainfall inside the rainy areas. The final rainfall estimates are obtained as the product of the estimates of these two random functions. However the published approach does not contain a method for estimation of uncertainties. The contribution of this paper is the presentation of the indicator maximum likelihood estimator from which the local conditional distribution of the rainfall value at any location may be derived using an ensemble approach. From the conditional distribution, representations of uncertainty such as the estimation variance and confidence intervals can be obtained. An approximation to the variance can be calculated more simply by assuming rainfall intensity is independent of location within the rainy area. The methodology has been validated using simulated and real rainfall data sets. The results of these case studies show good agreement between predicted uncertainties and measured errors obtained from the validation data.

Combining representations in working memory: A brief report

A task combining both digit and Corsi memory tests was administered to a group of 75 children. The task is shown to share variance with standardized reading and maths attainments, even after partialling out performance on component tasks separately assessed. The emergent task property may reflect coordination skills, although several different refinements can be made to this general conclusion.

The dangers of hanging baskets: 'Regulatory myths' and media representations of health and safety regulation

The successful enforcement of health and safety regulation is reliant upon the ability of regulatory agencies to demonstrate the legitimacy of the system of regulatory controls. While 'big cases' are central to this process, there are also significant legitimatory implications associated with 'minor' cases, including media-reported tales of pettiness and heavy-handedness in the interpretation and enforcement of the law. The popular media regularly report stories of 'regulatory unreasonableness', and they can pass quickly into mainstream public knowledge. A story's appeal becomes more important than its factual veracity; they are a form of 'regulatory myth'. This paper discusses the implications of regulatory myths for health and safety regulators, and analyses their challenges for regulators, paying particular attention to the Health and Safety Executive (HSE) which has made concerted efforts to address regulatory myths attaching to its activities. It will be shown that such stories constitute sustained normative challenges to the legitimacy of the regulator, and political challenges to the burgeoning regulatory state, because they reflect some of the key concerns of late-modern society.

General systems perspective on achieving continuous synergy in a project organisation

Studies of construction labour productivity have revealed that limited predictability and multi-agent social complexity make long-range planning of construction projects extremely inaccurate. Fire-fighting, a cultural feature of construction project management, social and structural diversity of involved permanent organizations, and structural temporality all contribute towards relational failures and frequent changes. The main purpose of this paper is therefore to demonstrate that appropriate construction planning may have a profound synergistic effect on structural integration of a project organization. Using the general systems theory perspective it is further a specific objective to investigate and evaluate organizational effects of changes in planning and potentials for achieving continuous project-organizational synergy. The newly developed methodology recognises that planning should also represent a continuous, improvement-leading driving force throughout a project. The synergistic effect of the process planning membership duality fostered project-wide integration, eliminated internal boundaries, and created a pool of constantly upgrading knowledge. It maintained a creative environment that resulted in a number of process-related improvements from all parts of the organization. As a result labour productivity has seen increases of more than 30%, profits have risen from an average of 12% to more than 18%, and project durations have been reduced by several days.

Comparing correlations of continuous observations from two independent populations using a sequential approach

A sequential study design generally makes more efficient use of available information than a fixed sample counterpart of equal power. This feature is gradually being exploited by researchers in genetic and epidemiological investigations that utilize banked biological resources and in studies where time, cost and ethics are prominent considerations. Recent work in this area has focussed on the sequential analysis of matched case-control studies with a dichotomous trait. In this paper, we extend the sequential approach to a comparison of the associations within two independent groups of paired continuous observations. Such a comparison is particularly relevant in familial studies of phenotypic correlation using twins. We develop a sequential twin method based on the intraclass correlation and show that use of sequential methodology can lead to a substantial reduction in the number of observations without compromising the study error rates. Additionally, our approach permits straightforward allowance for other explanatory factors in the analysis. We illustrate our method in a sequential heritability study of dysplasia that allows for the effect of body mass index and compares monozygotes with pairs of singleton sisters. Copyright (c) 2006 John Wiley & Sons, Ltd.

Bayesian decision procedures for binary and continuous bivariate dose-escalation studies

In this paper, Bayesian decision procedures are developed for dose-escalation studies based on binary measures of undesirable events and continuous measures of therapeutic benefit. The methods generalize earlier approaches where undesirable events and therapeutic benefit are both binary. A logistic regression model is used to model the binary responses, while a linear regression model is used to model the continuous responses. Prior distributions for the unknown model parameters are suggested. A gain function is discussed and an optional safety constraint is included. Copyright (C) 2006 John Wiley & Sons, Ltd.

Efficient and cost-effective experimental determination of kinetic constants and data: the success of a Bayesian systematic approach to drug transport, receptor binding, continuous culture and cell transport kinetics

Details about the parameters of kinetic systems are crucial for progress in both medical and industrial research, including drug development, clinical diagnosis and biotechnology applications. Such details must be collected by a series of kinetic experiments and investigations. The correct design of the experiment is essential to collecting data suitable for analysis, modelling and deriving the correct information. We have developed a systematic and iterative Bayesian method and sets of rules for the design of enzyme kinetic experiments. Our method selects the optimum design to collect data suitable for accurate modelling and analysis and minimises the error in the parameters estimated. The rules select features of the design such as the substrate range and the number of measurements. We show here that this method can be directly applied to the study of other important kinetic systems, including drug transport, receptor binding, microbial culture and cell transport kinetics. It is possible to reduce the errors in the estimated parameters and, most importantly, increase the efficiency and cost-effectiveness by reducing the necessary amount of experiments and data points measured. (C) 2003 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.