Ocean-floor hydrothermal metamorphism in the Limousin ophiolites (western French Massif Central): evidence of a rare preserved Variscan oceanic marker

The Limousin ophiolite is located at the suture zone between two major thrust sheets in the western French Massif Central. This ophiolitic section comprises mantle‐harzburgite, mantle‐dunite, wehrlites, troctolites and layered gabbros. It has recorded a static metamorphic event transforming the gabbros into undeformed amphibolites and the magmatic ultramafites into serpentinites and/or pargasite‐bearing chloritites. With various thermobarometric methods, it is possible to show that the different varieties of amphibole have registered low‐P (c. 0.2 GPa) conditions with temperature ranging from high‐T, late‐magmatic conditions to greenschist–zeolite metamorphic facies. The abundance of undeformed metamorphic rocks (which is typical of the lower oceanic crust), the occurrence of Ca–Al (–Mg) metasomatism illustrated by the growth of Ca–Al silicates in veins or replacing the primary magmatic minerals, the P–T conditions of the metamorphism and the numerous similarities with oceanic crustal rocks from Ocean Drilling Program and worldwide ophiolites are the main arguments for an ocean‐floor hydrothermal metamorphism in the vicinity of a palaeo‐ridge. Among the West‐European Variscan ophiolites, the Limousin ophiolites constitute an extremely rare occurrence that has not been involved in any HP (subduction‐related) or MP (orogenic) metamorphism as observed in other ophiolite occurrences (i.e. France, Spain and Germany).     

Estimation of dispersion in estuaries by a self-consistent method

Longitudinal and transverse dispersion in estuaries may be determined in principle by measuring the change in time of the concentration field of a water soluble dye. In practice, measurements may take the form of several sampling runs crossing the dye patch. The coefficients of dispersion are usually estimated from the second moments of the concentration field; the use of second moments, in particular, introduces errors because measurements at long times or distance are unduly emphasized.A self-consistent method, free of the disadvantages inherent in the use of higher moments, is described in which the distribution of concentration in space is related to the zeroth spatial moment of concentration. In this formulation, based upon sampling runs across the dye patch, the concentration field in the estuary may be directly and simply related to the dispersion coefficients in both the intercept and gradient of a linear graph.The methods are illustrated by the characterization of a series of experiments in the Inner Estuary of Milford Haven.     

Seasonal variations in prey selection by estuarine black-headed gulls (Larus ridibundus)

The number of black-headed gulls (Larus ridibundus) in the Clyde Estuary is large. In summer the average density has reached 1350 gulls km^?2 and in winter 180 gulls km^?2. This paper compares prey selection and feeding efficiency in gulls during summer and winter on tidal flats, and considers how seasonal differences may be adaptations to cope with seasonal changes in prey availability.Gross and net rates of energy intake were highest in summer because gulls captured more of the polychaete N. diversicolor than the amphipod C. volutator. In winter, gulls selected for C. volutator and therefore an energetically less profitable diet. Throughout the year gulls selected more C. volutator relative to N. diversicolor than expected on energetic grounds and so apparently did not maximize potential net rate of energy intake.Gulls used three techniques to capture prey and made most intensive use of the ‘crouch’ technique. Crouching gulls attained a much higher net rate of energy intake than ‘upright’ or ‘paddling’ gulls.A log-linear model showed that (a) season, water depth and gull density determined feeding technique and (b) feeding technique and season independently determined foraging success and prey selection. Thus gull density and water depth acted on prey selection through imposed variations in feeding technique.Reasons for gulls selecting energetically unprofitable C. volutator and for the use of several distinct feeding techniques are discussed.     

A neural network approach to ship track-keeping control

This paper presents an on-line trained neural net work controller for ship track-keeping problems. Following a brief review of the ship track-keeping control development since the 1980's, an analysis of various existing backpropagation-based neural controllers is provided. We then propose a single-input multioutput (SIMO) neural control strategy for situations where the exact mathematical dynamics of the ship are not available. The aim of this study is to build an autonomous neural controller which uses rudder to regulate both the tracking error and heading error. During the whole control process, the proposed SIMO neural controller adapts itself on-line from a direct evaluation of the control accuracy, and hence the need for a “teacher” or an off-line training process can be removed. With a relatively modest amount of quantitative knowledge of the ship behavior, the design philosophy enables real time control of a nonlinear ship model under random wind disturbances and measurement noise. Three different track-keeping tasks have been simulated to demonstrate the effectiveness of the training method and the robust performance of the proposed neural control strategy     

Type II bursts of different subclasses associated to transients and mass ejection in the higher corona

The list of mass ejections published in Solar Geophysical Data during the period of Jan. 1981 to Oct. 1987 contains about 1300 Surges, Sprays and Type II bursts. The relationship between the mass ejection events and the shock front events is investigated by means of correlation of time and position. The result shows that type II bursts start as frequently after the mass ejections as prior to them.     

Identification of physical processes inherent in artificial neural network rainfall runoff models

The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd.