Late-Pleistocene palaeoclimate and glacial activity recorded from lake sediments in the Eastern Alps

Greenland ice core data show that the last glaciation in the Northern Hemisphere was characterized by relatively short and rapid warming-cooling cycles. While the Last Glacial Maximum (LGM) and the following Late Glacial are well documented in the Eastern Alps, continuous and well dated records of the time period preceding the LGM are only known from stalagmites. Although most of the sediment that filled the Alpine valleys prior to the LGM was eroded, thick successions have been locally preserved as terraces along the flanks of large longitudinal valleys. The Inn valley in Tyrol (Austria) offers the most striking examples of Pleistocene terraces in the Eastern Alps. A large number of drill cores provides the opportunity to study these sediments for the first time in great detail. Our study focuses on the river terrace of Unterangerberg near Wörgl, where LGM gravel and till were deposited on top of (glacio)lacustrine sediments. The cores comprise mostly silty material, ranging from organic-rich to organic-poor and dropstone-rich beds. A diamictic layer classified as basal till is present at the bottom of the lake sediments. Radiocarbon ages of plant macro remains from the lake sequences indicate deposition between ~40 and >50 cal. ka BP. Luminescence ages obtained from fine-grain polymineral (4-11 μm) samples suggest an age of the lake deposits between ~40 to 60 ka and are consistent with the radiocarbon dates. Sedimentological analyses indicate that sedimentation in these palaeolakes was driven by local processes, but also by climatically induced changes in nearby glacier activity. These observations strongly hint towards a significant ice advance in the Eastern Alps during the early last glacial and subsequent mild interstadial conditions, supporting a local coniferous forest vegetation.

The VINEYARD Approach: Versatile, Integrated, Accelerator-Based, Heterogeneous Data Centres.

Emerging web applications like cloud computing, Big Data and social networks have created the need for powerful centres hosting hundreds of thousands of servers. Currently, the data centres are based on general purpose processors that provide high flexibility buts lack the energy efficiency of customized accelerators. VINEYARD aims to develop an integrated platform for energy-efficient data centres based on new servers with novel, coarse-grain and fine-grain, programmable hardware accelerators. It will, also, build a high-level programming framework for allowing end-users to seamlessly utilize these accelerators in heterogeneous computing systems by employing typical data-centre programming frameworks (e.g. MapReduce, Storm, Spark, etc.). This programming framework will, further, allow the hardware accelerators to be swapped in and out of the heterogeneous infrastructure so as to offer high flexibility and energy efficiency. VINEYARD will foster the expansion of the soft-IP core industry, currently limited in the embedded systems, to the data-centre market. VINEYARD plans to demonstrate the advantages of its approach in three real use-cases (a) a bio-informatics application for high-accuracy brain modeling, (b) two critical financial applications, and (c) a big-data analysis application.

Cloud Benchmarking For Maximising Performance of Scientific Applications

How can applications be deployed on the cloud to achieve maximum performance? This question is challenging to address with the availability of a wide variety of cloud Virtual Machines (VMs) with different performance capabilities. The research reported in this paper addresses the above question by proposing a six step benchmarking methodology in which a user provides a set of weights that indicate how important memory, local communication, computation and storage related operations are to an application. The user can either provide a set of four abstract weights or eight fine grain weights based on the knowledge of the application. The weights along with benchmarking data collected from the cloud are used to generate a set of two rankings - one based only on the performance of the VMs and the other takes both performance and costs into account. The rankings are validated on three case study applications using two validation techniques. The case studies on a set of experimental VMs highlight that maximum performance can be achieved by the three top ranked VMs and maximum performance in a cost-effective manner is achieved by at least one of the top three ranked VMs produced by the methodology.

Effective grain size distribution analysis for interpretation of tidal-deltaic facies: West Bengal Sundarbans

Research over the past two decades on the Holocene sediments from the tide dominated west side of the lower Ganges delta has focussed on constraining the sedimentary environment through grain size distributions (GSD). GSD has traditionally been assessed through the use of probability density function (PDF) methods (e.g. log-normal, log skew-Laplace functions), but these approaches do not acknowledge the compositional nature of the data, which may compromise outcomes in lithofacies interpretations. The use of PDF approaches in GSD analysis poses a series of challenges for the development of lithofacies models, such as equifinal distribution coefficients and obscuring the empirical data variability. In this study a methodological framework for characterising GSD is presented through compositional data analysis (CODA) plus a multivariate statistical framework. This provides a statistically robust analysis of the fine tidal estuary sediments from the West Bengal Sundarbans, relative to alternative PDF approaches.

Ultra-High-Resolution Observations of MHD Waves in Photospheric Magnetic Structures

This chapter reviews the recent observations of waves and oscillations manifesting in fine-scale magnetic structures in the solar photosphere, which are often interpreted as the "building blocks' of the magnetic Sun. The authors found, through phase relationships between the various waveforms, that small-scale magnetic bright points (MBPs) in the photosphere demonstrated signatures of specific magnetoacoustic waves, in particular the sausage and kink modes. Modern magnetohydrodynamic (MHD) simulations of the lower solar atmosphere clearly show how torsional motions can easily be induced in magnetic elements in the photosphere through the processes of vortical motions and/or buffeting by neighboring granules. The authors detected significant power associated with high-frequency horizontal motions, and suggested that these cases may be especially important in the creation of a turbulent environment that efficiently promotes Alfvén wave dissipation.