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Lipid droplets (LDs) are the major fat storage organelles in eukaryotic cells, but how their size is regulatedis unknown. Using genetic screens in C.elegans for LD morphology defects in intestinal cells, we found that mutations in atlastin, a GTPase required for homotypic fusion of endoplasmic reticulum (ER) membranes, cause not only ER morphology defects, but also a reduction in LD size. Similar results were obtained after depletion of atlastin or expression of a dominant-negative mutant, whereas overexpression of atlastin had the opposite effect. Atlastin depletion in Drosophila fat bodies also reduced LD size and decreased triglycerides in whole animals, sensitizing them to starvation. In mammalian cells, co-overexpression of atlastin-1 and REEP1, a paralog of the ER tubule-shaping protein DP1/REEP5, generates large LDs. The effect of atlastin-1 on LD size correlates with its activity to promote membrane fusion invitro. Our results indicate that atlastin-mediated fusion of ER membranes is important for LD size regulation. © 2013 The Authors.

In order to use environmental models effectively for management and decision-making, it is vital to establish an appropriate level of confidence in their performance. This paper reviews techniques available across various fields for characterising the performance of environmental models with focus on numerical, graphical and qualitative methods. General classes of direct value comparison, coupling real and modelled values, preserving data patterns, indirect metrics based on parameter values, and data transformations are discussed. In practice environmental modelling requires the use and implementation of workflows that combine several methods, tailored to the model purpose and dependent upon the data and information available. A five-step procedure for performance evaluation of models is suggested, with the key elements including: (i) (re)assessment of the model's aim, scale and scope; (ii) characterisation of the data for calibration and testing; (iii) visual and other analysis to detect under- or non-modelled behaviour and to gain an overview of overall performance; (iv) selection of basic performance criteria; and (v) consideration of more advanced methods to handle problems such as systematic divergence between modelled and observed values.

Throughout the last decades uncertainty analysis has become an essential part of environmental model building (e.g. Beck 1987; Refsgaard et al., 2007). The objective of the paper is to introduce stochastic and setmembership uncertainty modelling concepts, which basically differ in the assumptions that are made with respect to the uncertainty characterization. Stochastic uncertainty modelling is most frequently applied and is characterized by probability density functions (pdf’s) or simply by means and (co)variances. Typical approaches are the Bayesian and the Monte Carlo Markov Chain methods. Alternatively, a set-membership or bounded-error characterization, as opposed to a stochastic characterization, is favoured when assumptions about distribution or estimates of mean and covariance cannot be satisfactorily tested, as with small data sets or heavily structured (modelling) errors. The bounded-error characterization is in essence deterministic. Both approaches, using tools as DREAM, GLUE, exact and approximate bounding, MCSM and a pavement-based technique, were tested on a real-world example. The example, based on Wasson’s (1994) sediment yield – area data and after a log-log transformation of the data, is a linear static problem with two parameters.

Models have become indispensable in environmental assessment, planning and management. However as models have increasingly been developed and disseminated, the risk of their misuse or misunderstanding of their capabilities has increased. Whether a model is used for simulation, prediction, decision making or communication of scientific analyses, it is important that its development and application conform to protocols or standards that help to maximise the scientific soundness, utility and defensibility of models and their outputs. The complexity and uncertainty inherent in environmental assessment make the pursuit of good modelling practice especially important, in spite of limited time and resources. This paper is an attempt to identify the key components of best modelling practice and our collective progress in its achievement, taking into account previous relevant reviews undertaken by several authors and agencies. The details are always likely to be the subject of lively debate, but the general components of ‘good modelling practice’ are probably not controversial. They are clear purpose, adequate reporting, and serious evaluation. Although these are common strands in the various definitions of good modelling practice the emphasis varies between different types of model application. For this reason it is important that good practice should not become overly prescriptive.We report a preliminary analysis which suggests that progress towards improving modelling practice is slow. This is despite very widespread agreement on what constitutes good practice. Why is this so? In the research community at least, the drivers for model development and evaluation are funding and publication. If modelling practice needs to be improved, and we think it does, sponsors and journals need to take a lead in creating an environment where developing a model requires that the work be undertaken under some system of good modelling practice. The suggestion has been made of a ‘good pract

Conflict occurs when two or more trains approach the same junction within a specified time. Such conflicts result in delays. Current practices to assign the right of way at junctions achieve orderly and safe passage of the trains, but do not attempt to reduce the delays. A traffic controller developed in the paper assigns right of way to impose minimum total weighted delay on the trains. The traffic flow model and the optimisation technique used in this controller are described. Simulation studies of the performance of the controller are given.

This paper introduces an event-based traffic model for railway systems adopting fixed-block signalling schemes. In this model, the events of trains' arrival at and departure from signalling blocks constitute the states of the traffic flow. A state transition is equivalent to the progress of the trains by one signalling block and it is realised by referring to past and present states, as well as a number of pre-calculated look-up tables of run-times in the signalling block under various signalling conditions. Simulation results are compared with those from a time-based multi-train simulator to study the improvement of processing time and accuracy.