A Novel Prediction Setup for Online Speed-Scaling

Given the rapid rise in energy demand by data centers and computing systemsin general, it is fundamental to incorporate energy considerations whendesigning (scheduling) algorithms. Machine learning can be a useful approach inpractice by predicting the future load of the system based on, for example,historical data. However, the effectiveness of such an approach highly dependson the quality of the predictions and can be quite far from optimal whenpredictions are sub-par. On the other hand, while providing a worst-caseguarantee, classical online algorithms can be pessimistic for large classes ofinputs arising in practice. This paper, in the spirit of the new area of machine learning augmentedalgorithms, attempts to obtain the best of both worlds for the classical,deadline based, online speed-scaling problem: Based on the introduction of anovel prediction setup, we develop algorithms that (i) obtain provably lowenergy-consumption in the presence of adequate predictions, and (ii) are robustagainst inadequate predictions, and (iii) are smooth, i.e., their performancegradually degrades as the prediction error increases.<br

Lingulodinium machaerophorum expansion over the last centuries in the Caspian Sea reflects global warming

This article is made available through the Brunel Open Access Publishing Fund. Copyright @ Author(s) 2012. This work is distributed under the Creative Commons Attribution 3.0 License.We analysed dinoflagellate cyst assemblages in four short sediment cores, two of them dated by radionuclides, taken in the south basin of the Caspian Sea. The interpretation of the four sequences is supported by a collection of 27 lagoonal or marine surface sediment samples. A sharp increase in the biomass of the dinocyst occurs after 1967, especially owing to Lingulodinium machaerophorum. Considering nine other cores covering parts or the whole of Holocene, this species started to develop in the Caspian Sea only during the last three millennia. By analysing instrumental data and collating existing reconstructions of sea level changes over the last few millennia, we show that the main forcing of the increase of L. machaerophorum percentages and of the recent dinocyst abundance is global climate change, especially sea surface temperature increase. Sea level fluctuations likely have a minor impact. We argue that the Caspian Sea has entered the Anthropocene

A highly efficient green synthesis of 1, 8-dioxo-octahydroxanthenes

SmCl3 (20 mol%) has been used as an efficient catalyst for reaction between aromatic aldehydes and 5,5-dimethyl-1,3-cyclohexanedione at 120°C to give 1,8-dioxo-octahydroxanthene derivatives in high yield. The same reaction in water, at room temperature gave only the open chain analogue of 1,8-dioxo-octahydroxanthene. Use of eco-friendly green Lewis acid, readily available catalyst and easy isolation of the product makes this a convenient method for the synthesis of either of the products

Numerical modelling of an embankment dam

SIGLEAvailable from British Library Document Supply Centre- DSC:DX79370 / BLDSC - British Library Document Supply CentreGBUnited Kingdo