FAME, A Polyglot Library for Metamodeling at Runtime

Tomorrow's eternal software system will co-evolve with their context: their metamodels must adapt at runtime to ever-changing external requirements. In this paper we present FAME, a polyglot library that keeps metamodels accessible and adaptable at runtime. Special care is taken to establish causal connection between fame-classes and host-classes. As some host-languages offer limited reflection features only, not all implementations feature the same degree of causal connection. We present and discuss three scenarios: 1) full causal connection, 2) no causal connection, and 3) emulated causal connection. Of which, both Scenario 1 and 3 are suitable to deploy fully metamodel-driven applications.

A TEX 86 lake record suggests simultaneous shifts in temperature in Central Europe and Greenland during the last deglaciation

High-resolution quantitative temperature records from continents covering glacial to interglacial transitions are scarce but important for understanding the climate system. We present the first decadal resolution record of continental temperatures in Central Europe during the last deglaciation (similar to 14,60010,600cal. yrB.P.) based on the organic geochemical palaeothermometer TEX86. The TEX86-inferred temperature record from Lake Lucerne (Vierwaldstattersee, Switzerland) reveals typical oscillations during the Late Glacial Interstadial, followed by an abrupt cooling of 2 degrees C at the onset of Younger Dryas and a rapid warming of 4 degrees C at the onset of the Holocene, within less than 350years. The remarkable resemblance with the Greenland and regional stable oxygen isotope records suggests that temperature changes in continental Europe were dominated by large-scale reorganizations in the northern hemispheric climate system.

Building a soil spectral library for Tajikistan comparing local and global modeling approaches

Over the last ~20 years, soil spectral libraries storing near-infrared reflectance (NIR) spectra from diverse soil samples have been built for many places, since almost 10 years also for Tajikistan. Many calibration approaches have been reported and used for prediction from large and heterogeneous libraries, but most are hampered by the high diversity of the soils, where the mineral background is heavily influencing spectral features. In such cases, local learning strategies have the advantage of building locally adapted calibrations, which can deal better with nonlinearities. Therefore, it was our major aim to identify the most efficient approach to develop an accurate and stable locally weigthed calibration model using a spectral library compiled over the past years. Keywords: Tajikistan, Near-Infrared spectroscopy (NIRS), soil organic carbon, locally weighted regression, regional and local spectral library.