Modelling the growth and movement of cyanobacteria in river systems

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes and rivers. In this article, a new deterministic model is introduced which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the four major factors that affect the cyanobacterial bloom formation in freshwaters: light, nutrients, temperature and river flow. The model consists of two sub-models: a vertical migration model with respect to growth of cyanobacteria in relation to light, nutrients and temperature; and a hydraulic model to simulate the horizontal movement of the bloom. This article presents the model algorithms and highlights some important model results. The effects of nutrient limitation, varying illumination and river flow characteristics on cyanobacterial movement are simulated. The results indicate that under high light intensities and in nutrient-rich waters colonies sink further as a result of carbohydrate accumulation in the cells. In turbulent environments, vertical migration is retarded by vertical velocity component generated by turbulent shear stress. (c) 2006 Elsevier B.V. All rights reserved.

Survival, Pb-uptake and behaviour of three species of earthworm in Pb treated soils determined using an OECD-style toxicity test and a soil avoidance test

Mature (clitellate) Eisenia andrei Bouche (ultra epigeic), Lumbricus rubellus Hoffmeister (epigeic), and Aporrectodea caliginosa (Savigny) (endogeic) earthworms were placed in soils treated with Pb(NO3)(2) to have concentrations in the range 1000 to 10 000 mg Pb kg(-1). After 28 days LC50(-95%confidence limit) (+95%confidence limit) values were E. andrei 5824(-361)(+898) mg Pb kg(-1), L. rubellus 2867(-193)(+145) mg Pb kg(-1) and A. caliginosa 2747(-304)(+239) mg Pb kg(-1) and EC50s for weight change were E. andrei 2841(-68)(+150) Pb kg(-1), L. rubellus 1303(-201)(+204) mg Pb kg(-1) and A. caliginosa 1208(-206)(+212) Mg Pb kg(-1). At any given soil Pb concentration, Pb tissue concentrations after 28 days were the same for all three earthworm species. In a soil avoidance test there was no difference between the behaviour of the different species. The lower sensitivity to Pb exhibited by E. andrei is most likely due to physiological adaptations associated with the modes of life of the earthworms, and could have serious implications for the use of this earthworm as the species of choice in standard toxicological testing. (c) 2005 Elsevier Ltd. All rights reserved.

Minimum aberration construction results for nonregular two-level fractional factorial designs

Nonregular two-level fractional factorial designs are designs which cannot be specified in terms of a set of defining contrasts. The aliasing properties of nonregular designs can be compared by using a generalisation of the minimum aberration criterion called minimum G2-aberration.Until now, the only nontrivial designs that are known to have minimum G2-aberration are designs for n runs and m n–5 factors. In this paper, a number of construction results are presented which allow minimum G2-aberration designs to be found for many of the cases with n = 16, 24, 32, 48, 64 and 96 runs and m n/2–2 factors.

Sparse modeling using orthogonal forward regression with PRESS statistic and regularization

The paper introduces an efficient construction algorithm for obtaining sparse linear-in-the-weights regression models based on an approach of directly optimizing model generalization capability. This is achieved by utilizing the delete-1 cross validation concept and the associated leave-one-out test error also known as the predicted residual sums of squares (PRESS) statistic, without resorting to any other validation data set for model evaluation in the model construction process. Computational efficiency is ensured using an orthogonal forward regression, but the algorithm incrementally minimizes the PRESS statistic instead of the usual sum of the squared training errors. A local regularization method can naturally be incorporated into the model selection procedure to further enforce model sparsity. The proposed algorithm is fully automatic, and the user is not required to specify any criterion to terminate the model construction procedure. Comparisons with some of the existing state-of-art modeling methods are given, and several examples are included to demonstrate the ability of the proposed algorithm to effectively construct sparse models that generalize well.

Interventions to promote healthy eating habits: evaluation and recommendations

Although in several EU Member States many public interventions have been running for the prevention and/or management of obesity and other nutrition-related health conditions, few have yet been formally evaluated. The multidisciplinary team of the EATWELL project will gather benchmark data on healthy eating interventions in EU Member States and review existing information on the effectiveness of interventions using a three-stage procedure (i) Assessment of the intervention's impact on consumer attitudes, consumer behaviour and diets; (ii) The impact of the change in diets on obesity and health and (iii) The value attached by society to these changes, measured in life years gained, cost savings and quality-adjusted life years. Where evaluations have been inadequate, EATWELL will gather secondary data and analyse them with a multidisciplinary approach incorporating models from the psychology and economics disciplines. Particular attention will be paid to lessons that can be learned from private sector that are transferable to the healthy eating campaigns in the public sector. Through consumer surveys and workshops with other stakeholders, EATWELL will assess the acceptability of the range of potential interventions. Armed with scientific quantitative evaluations of policy interventions and their acceptability to stakeholders, EATWELL expects to recommend more appropriate interventions for Member States and the EU, providing a one-stop guide to methods and measures in interventions evaluation, and outline data collection priorities for the future.

A Gaussian-mixture ensemble transform filter

We generalize the popular ensemble Kalman filter to an ensemble transform filter, in which the prior distribution can take the form of a Gaussian mixture or a Gaussian kernel density estimator. The design of the filter is based on a continuous formulation of the Bayesian filter analysis step. We call the new filter algorithm the ensemble Gaussian-mixture filter (EGMF). The EGMF is implemented for three simple test problems (Brownian dynamics in one dimension, Langevin dynamics in two dimensions and the three-dimensional Lorenz-63 model). It is demonstrated that the EGMF is capable of tracking systems with non-Gaussian uni- and multimodal ensemble distributions. Copyright © 2011 Royal Meteorological Society

The financial effects of uniform and mixed corporate social performance

Firms typically present a mixed picture of corporate social performance (CSP), with positive and negative indicators exhibited by the same firm. Thus, stakeholders’ judgements of corporate social responsibility (CSR) typically evaluate positives in the context of negatives, and vice versa. Building on social judgement theory, we present two alternative accounts of how stakeholders respond to such complexity, which provide differing implications for the financial effects of CSP: reciprocal dampening and rewarding uniformity. Echoing notable findings on strategic consistency, our US panel study finds that firms that exhibit uniformly positive or uniformly negative indicators in particular dimensions of CSP outperform firms that exhibit a mixed picture of positives and negatives, which supports the notion that stakeholders’ judgements of CSR reward uniformity.