Improved understanding of dynamic water and mass budgets of high‐alpine karst systems obtained from studying a well‐defined catchment area

Large areas of Europe, especially in the Alps, are covered by carbonate rocks and in many alpine regions, karst springs are important sources for drinking water supply. Because of their high variability and heterogeneity, the understanding of the hydrogeological functioning of karst aquifers is of particular importance for their protection and utilisation. Climate change and heavy rainfall events are major challenges in managing alpine karst aquifers which possess an enormous potential for future drinking water supply. In this study, we present research from a high‐alpine karst system in the UNESCO Biosphere Reserve Großes Walsertal in Austria, which has a clearly defined catchment and is drained by only one spring system. Results show that (a) the investigated system is a highly dynamic karst aquifer with distinct reactions to rainfall events in discharge and electrical conductivity; (b) the estimated transient atmospheric CO2 sink is about 270 t/a; (c) the calculated carbonate rock denudation rate is between 23 and 47 mm/1000a and (d) the rainfall‐discharge behaviour and the internal flow dynamics can be successfully simulated using the modelling package KarstMod. The modelling results indicate the relevance of matrix storage in determining the discharge behaviour of the spring, particularly during low‐flow periods. This research and the consequent results can contribute and initiate a better understanding and management of alpine karst aquifers considering climate change with more heavy rainfall events and also longer dry periods.The investigated karst system contributes to the transient atmospheric CO2 sink with about 270 t/a. Carbonate denudation rates vary between 23 and 47 mm/1000a. Rainfall‐discharge modelling results indicate the importance of matrix storage particularly during low‐flow periods. imageBundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347FP7 People: Marie‐Curie Actions http://dx.doi.org/10.13039/10001126

Strain-Based Analysis for Geometrically Nonlinear Beams: A Modal Approach

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97066/1/AIAA2012-1713.pd

Social navigation

In this chapter we present one of the pioneer approaches in supporting users in navigating the complex information spaces, social navigation support. Social navigation support is inspired by natural tendencies of individuals to follow traces of each other in exploring the world, especially when dealing with uncertainties. In this chapter, we cover details on various approaches in implementing social navigation support in the information space as we also connect the concept to supporting theories. The first part of this chapter reviews related theories and introduces the design space of social navigation support through a series of example applications. The second part of the chapter discusses the common challenges in design and implementation of social navigation support, demonstrates how these challenges have been addressed, and reviews more recent direction of social navigation support. Furthermore, as social navigation support has been an inspirational approach to various other social information access approaches we discuss how social navigation support can be integrated with those approaches. We conclude with a review of evaluation methods for social navigation support and remarks about its current state

A Regression Tree Approach using Mathematical Programming

Regression analysis is a machine learning approach that aims to accurately predict the value of continuous output variables from certain independent input variables, via automatic estimation of their latent relationship from data. Tree-based regression models are popular in literature due to their flexibility to model higher order non-linearity and great interpretability. Conventionally, regression tree models are trained in a two-stage procedure, i.e. recursive binary partitioning is employed to produce a tree structure, followed by a pruning process of removing insignificant leaves, with the possibility of assigning multivariate functions to terminal leaves to improve generalisation. This work introduces a novel methodology of node partitioning which, in a single optimisation model, simultaneously performs the two tasks of identifying the break-point of a binary split and assignment of multivariate functions to either leaf, thus leading to an efficient regression tree model. Using six real world benchmark problems, we demonstrate that the proposed method consistently outperforms a number of state-of-the-art regression tree models and methods based on other techniques, with an average improvement of 7–60% on the mean absolute errors (MAE) of the predictions

Species diversity of Trichoderma in Poland

In the present study, we reinvestigate the diversity of Trichoderma in Poland utilizing a combination of morphological and molecular/phylogenetic methods. A total of 170 isolates were collected from six different substrata at 49 sites in Poland. These were divided among 14 taxa as follows: 110 of 170 Trichoderma isolates were identified to the species level by the analysis of their ITS1, ITS2 rDNA sequences as: T. harzianum (43 isolates), T. aggressivum (35), T. citrinoviride (11), T. hamatum (9), T. virens (6), T. longibrachiatum (4), T. polysporum (1), and T. tomentosum (1); 60 isolates belonging to the Viride clade were identified based on a fragment of the translation-elongation factor 1-alpha (tef1) gene as: T. atroviride (20 isolates), T. gamsii (2), T. koningii (17), T. viridescens (13), T. viride (7), and T. koningiopsis (1). Identifications were made using the BLAST interface in TrichOKEY and TrichoBLAST (http://www.isth.info). The most diverse substrata were soil (nine species per 22 isolates) and decaying wood (nine species per 75 isolates). The most abundant species (25%) isolated from all substrata was T. harzianum

Quaternary glacial history of the Mediterranean mountains

Glacial and periglacial landforms are widespread in the mountains of the Mediterranean region. The evidence for glacial and periglacial activity has been studied for over 120 years and it is possible to identify three phases of development in this area of research. First, a pioneer phase characterized by initial descriptive observations of glacial landforms; second, a mapping phase whereby the detailed distribution of glacial landforms and sediments have been depicted on geomorphological maps; and, third, an advanced phase characterized by detailed understanding of the geochronology of glacial sequences using radiometric dating alongside detailed sedimentological and stratigraphical analyses. It is only relatively recently that studies of glaciated mountain terrains in the Mediterranean region have reached an advanced phase and it is now clear from radiometric dating programmes that the Mediterranean mountains have been glaciated during multiple glacial cycles. The most extensive phases of glaciation appear to have occurred during the Middle Pleistocene. This represents a major shift from earlier work whereby many glacial sequences were assumed to have formed during the last cold stage. Glacial and periglacial deposits from multiple Quaternary cold stages constitute a valuable palaeoclimatic record. This is especially so in the Mediterranean mountains, since mountain glaciers in this latitudinal zone would have been particularly sensitive to changes in the global climate system. © 2006 Edward Arnold (Publishers) Ltd