Effects of water-borne copper on metallothionein and lipid peroxidation in the marine amphipod Gammarus locusta

The aim of the current work was to determine over 10 days the effects of water-borne exposure of the marine amphipod Gammarus locusta to 4 microgCu l(-1) on the metallothionein (MT; measured by differential pulse polarography) protection system and lipid peroxidation (LP: thiobarbituric acid-reactive malondialdehyde equivalents) as a measure of oxidative damage. MT levels in exposed animals increased significantly at day 2 (36% > control; P < 0.001) and remained high at days 6 and 10 (55 and 38%, respectively, P < 0.001). The maximum level of MT at day 6 coincided with the highest Cu body-burden. LP increased within I day of exposure, indicative of Cu as an oxidative stressor. However, in contrast to MT, the highest LP level was seen at day 4 (68% > control, P < 0.001) before returning to control values by day 6, indicating a protective role of MT against the pro-oxidant effects of Cu.     

Evaluation of long-term extreme response statistics of jack-up platforms

This paper is concerned with the models appropriate for the dynamic assessment of jack-ups, concentrating particularly on the long-term response due to random ocean waves and on work-hardening plasticity models used for spud-can response. A methodology for scaling of short-term statistics, calculated using a Constrained NewWave technique, is shown in a numerical experiment for an example jack-up and central North Sea location. The difference in long-term extreme response statistics due to various footing assumptions is emphasised. Results for two environmental load conditions are described (one excluding and one including wind and current effects) and the role of sea-state severity in the variation of short-term extreme response statistics is also highlighted.     

Characterizing Observed Environmental Variability With HF Doppler Radar Surface Current Mappers and Acoustic Doppler Current Profilers: Environmental Variability in the Coastal Ocean

A network of high-frequency (HF) radars is deployed along the New Jersey coast providing synoptic current maps across the entire shelf. These data serve a variety of user groups from scientific research to Coast Guard search and rescue. In addition, model forecasts have been shown to improve with surface current assimilation. In all applications, there is a need for better definitions and assessment of the measurement uncertainty. During a summer coastal predictive skill experiment in 2001, an array of in situ current profilers was deployed near two HF radar sites, one long-range and one standard-range system. Comparison statistics were calculated between different vertical bins on the same current profiler, between different current profilers, and between the current profilers and the different HF radars. The velocity difference in the vertical and horizontal directions were then characterized using the observed root-mean-square (rms) differences. We further focused on two cases, one with relatively high vertical variability, and the second with relatively low vertical variability. Observed differences between the top bin of the current profiler and the HF radar were influenced by both system accuracy and the environment. Using the in situ current profilers, the environmental variability over scales based on the HF radar sampling was quantified. HF radar comparisons with the current profilers were on the same order as the observed environmental difference over the same scales, indicating that the environment has a significant influence on the observed differences. Velocity variability in the vertical and horizontal directions both contribute to these differences. When the potential effects of the vertical variability could be minimized, the remaining difference between the current profiler and the HF radar was similar to the measured horizontal velocity difference (~2.5 cm/s) and below the resolution of the raw radial data at the time of the deployment     

Filters for linear sea-wave prediction

Deterministic sea-wave prediction (DSWP) models are appearing in the literature designed for quiescent interval prediction in marine applications dominated by large swell seas. The approach has focused upon spectral methods which are straightforward and intuitively attractive. However, such methods have the disadvantage that while the sea is aperiodic in nature, the standard discrete spectral processing techniques force an absolutely periodic structure onto the resulting sea surface prediction models. As it is the shape of the sea surface that is important in such applications, particularly near the end of the domain which is important, the standard windowing techniques used in signal processing work to reduce leakage artifacts cannot be employed. This has necessitated the use of end matching methods that can be both inconvenient and may reduce the fraction of the time for which legitimate predictions are available. As a result, an investigation has been undertaken of the use of finite impulse response prediction filters to provide the necessary dispersive phase shifting required in DSWP systems. The present work examines the theoretical basis for such filters and explores their properties together with their application to both long and short crested swell seas. It is shown that wide band forms of such filters are only convergent in the sense of distributions having both infinite duration impulse responses and asymptotically divergent first derivatives. However, appropriate band limitation can produce useful finite impulse responses allowing implementation via standard discrete convolution methods. It is demonstrated that despite the prediction filters having a non-causal impulse response such filters can be used in practice due to a combination of the asymmetric nature of the impulse response and the fundamental nature of the prediction process. The findings are confirmed against actual sea-wave data.