Suchergebnisse

Elections play a crucial role in post-conflict peace and democratization processes as, among other factors, they provide an answer to the question of who is to legitimately rule the country. However, because of the competitiveness arising from their central role in allocating power they can also represent windows of vulnerability where deeply rooted societal conflicts can come to the surface. This working paper focuses on two post-conflict elections (Sierra Leone 2007; Nepal 2008) which, despite perceived high risks, did not result in widespread violence or a return to armed conflict. The aim of these case studies is to identify the factors and measures that may have played an important role in contributing to this outcome. Each of the two case studies first outlines the risks associated with the elections and then analyzes the violence and conflict preventing factors. The paper shows that that the context greatly influences the type of measures that can be taken in such situations, but that there are also some similarities in the two cases studied. In particular, it appears that that the credibility of the elections, largely attributable to a good electoral administration, was an important factor in both Nepal and Sierra Leone. Furthermore, the inclusion of all key stakeholders in decisions regarding key electoral institutions helped to diffuse potential conflict. The study also shows that in both cases the international community played an important role by providing financial, logistical and technical support and by pressuring certain important actors to comply with the rules.

Distillers dried grains and solubles (DDGS) were investigated with attenuated total reflection FT-IR spectroscopy both directly in their solid state and as the isolated oils (fat fractions). The collected spectra were evaluated in a first step with principal component analysis (PCA) according to the botanical origin (corn, rice, wheat) and the geographical origin (Canada, China, European Union, India, United States) of the DDGS. In a second step, statistical models were constructed for the characterization of the botanical and geographical origin using linear discriminant analysis (LDA) and soft independent modeling of class analogy (SIMCA). For this purpose, the botanical origin was investigated more deeply for corn and wheat as the most important raw materials used for DDGS production. Also, the geographical origin was investigated exemplary for corn DDGS, derived from China and the United States. Models were validated by a randomized batchwise procedure and showed satisfactory classification rates, in most cases better than 80% correct classification