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.

Knowledge Management Techniques to Augment Textual CBR (PhD Thesis)

The past decade had witnessed an unprecedented growth in the amount of available digital content, and its volume is expected to continue to grow the next few years. Unstructured text data generated from web and enterprise sources form a large fraction of such content. Many of these contain large volumes of reusable data such as solutions to frequently occurring problems, and general know-how that may be reused in appropriate contexts. In this work, we address issues around leveraging unstructured text data from sources as diverse as the web and the enterprise within the Case-based Reasoning framework. Case-based Reasoning (CBR) provides a framework and methodology for systematic reuse of historical knowledge that is available in the form of problemsolution
pairs, in solving new problems. Here, we consider possibilities of enhancing Textual CBR systems under three main themes: procurement, maintenance and retrieval. We adapt and build upon the stateof-the-art techniques from data mining and natural language processing in addressing various challenges therein. Under procurement, we investigate the problem of extracting cases (i.e., problem-solution pairs) from data sources such as incident/experience
reports. We develop case-base maintenance methods specifically tuned to text targeted towards retaining solutions such that the utility of the filtered case base in solving new problems is maximized. Further, we address the problem of query suggestions for textual case-bases and show that exploiting the problem-solution partition can enhance retrieval effectiveness by prioritizing more useful query suggestions. Additionally, we illustrate interpretable clustering as a tool to drill-down to domain specific text collections (since CBR systems are usually very domain specific) and develop techniques for improved similarity assessment in social media sources such as microblogs. Through extensive empirical evaluations, we illustrate the improvements that we are able to
achieve over the state-of-the-art methods for the respective tasks.