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Welchen Aufgaben soll sich die NATO zuwenden? Wo soll sie enden? Als klassisches Militärbündnis verliert sie jedenfalls an Bedeutung. Die gegenwärtige Krise der regionalen Allianz mit globaler Reichweite muss genutzt werden für eine strategische Neuausrichtung der Struktur und Funktion des Bündnisses. Die Rolle der NATO als Werkzeug für multinationale Interventionen entscheidet über die Bildung globaler Koalitionen.
Background: Very recently a gene marker panel that allows the mutational analysis of APC, CTNNB1, B-RAF and K-RAS was conceived. The aim of the present study was to use the 4-gene marker panel covering the Wnt and Ras-Raf-MEK-MAPK signalling pathways to determine the percentage of sporadic colorectal carcinomas (CRC) carrying at least one of the four above-mentioned genes in a mutated form alone and/or in combination with microsatellite instability (MSI) and to compare the sensitivity of the gene marker panel used in this study with that of gene marker panels previously reported in the scientific literature. Methods: CTNNB1 and B-RAF were screened by PCR-single-strand conformation polymorphism analysis and K-RAS gene mutations by restriction fragment length polymorphism analysis. For the mutational analysis of the APC gene mutation cluster region (codons 1243–1567) direct DNA sequencing was performed. The U.S. National Cancer Institute microsatellite panel (BAT25, BAT26, D2S123, D5S346 and D17S250) was used for MSI analysis. Results: It could be shown that about 80% of early stage CRC (UICC stages I and II) and over 90% of CRC in the UICC stage IV carried at least one mutated gene and/or showed MSI. No significant increase in the gene mutation frequencies could be determined when comparing tumours in the UICC stage I with those in UICC stage IV. Conclusions: When compared with previously published gene marker panels the 4-gene marker panel used in the present study shows an excellent performance, allowing to detect genetic alterations in 80–90% of human sporadic CRC samples analyzed.
We examined individual differences in masked repetition priming by re-analyzing item-level response-time (RT) data from three experiments. Using a linear mixed model (LMM) with subjects and items specified as crossed random factors, the originally reported priming and word-frequency effects were recovered. In the same LMM, we estimated parameters describing the distributions of these effects across subjects. Subjects’ frequency and priming effects correlated positively with each other and negatively with mean RT. These correlation estimates, however, emerged only with a reciprocal transformation of RT (i.e., -1/RT), justified on the basis of distributional analyses. Different correlations, some with opposite sign, were obtained (1) for untransformed or logarithmic RTs or (2) when correlations were computed using within-subject analyses. We discuss the relevance of the new results for accounts of masked priming, implications of applying RT transformations, and the use of LMMs as a tool for the joint analysis of experimental effects and associated individual differences.
A macro-tidal freshwater ecosystem recovering from hypereutrophication : the Schelde lease study
(2009)
We report a 40 year record of eutrophication and hypoxia on an estuarine ecosystem and its recovery from hypereutrophication. After decades of high inorganic nutrient concentrations and recurring anoxia and hypoxia, we observe a paradoxical increase in chlorophyll-a concentrations with decreasing nutrient inputs. We hypothesise that algal growth was inhibited due to hypereutrophication, either by elevated ammonium concentrations, severe hypoxia or the production of harmful substances in such a reduced environment. We study the dynamics of a simple but realistic mathematical model, incorporating the assumption of algal growth inhibition. It shows a high algal biomass, net oxygen production equilibrium with low ammonia inputs, and a low algal biomass, net oxygen consumption equilibrium with high ammonia inputs. At intermediate ammonia inputs it displays two alternative stable states. Although not intentional, the numerical output of this model corresponds to observations, giving extra support for assumption of algal growth inhibition. Due to potential algal growth inhibition, the recovery of hypereutrophied systems towards a classical eutrophied state, will need reduction of waste loads below certain thresholds and will be accompanied by large fluctuations in oxygen concentrations. We conclude that also flow-through systems, heavily influenced by external forcings which partly mask internal system dynamics, can display multiple stable states.
Normal aging is associated with a decline in different cognitive domains and local structural atrophy as well as decreases in dopamine concentration and receptor density. To date, it is largely unknown how these reductions in dopaminergic neurotransmission affect human brain regions responsible for reward-based decision making in older adults. Using a learning criterion in a probabilistic object reversal task, we found a learning stage by age interaction in the dorsolateral prefrontal cortex (dIPFC) during decision making. While young adults recruited the dlPFC in an early stage of learning reward associations, older adults recruited the dlPFC when reward associations had already been learned. Furthermore, we found a reduced change in ventral striatal BOLD signal in older as compared to younger adults in response to high probability rewards. Our data are in line with behavioral evidence that older adults show altered stimulus-reward learning and support the view of an altered fronto-striatal interaction during reward-based decision making in old age, which contributes to prolonged learning of reward associations.
With the increasing availability of observational data from different sources at a global level, joint analysis of these data is becoming especially attractive. For such an analysis – oftentimes with little prior knowledge about local and global interactions between the different observational variables at hand – an exploratory, data-driven analysis of the data may be of particular relevance. In the present work we used generalized additive models (GAM) in an exemplary study of spatio-temporal patterns in the tropospheric NO2-distribution derived from GOME satellite observations (1996 to 2001) at global scale. We focused on identifying correlations between NO2 and local wind fields, a quantity which is of particular interest in the analysis of spatio-temporal interactions. Formulating general functional, parametric relationships between the observed NO2 distribution and local wind fields, however, is difficult – if not impossible. So, rather than following a modelbased analysis testing the data for predefined hypotheses (assuming, for example, sinusoidal seasonal trends), we used a GAM with non-parametric model terms to learn this functional relationship between NO2 and wind directly from the data. The NO2 observations showed to be affected by winddominated processes over large areas. We estimated the extent of areas affected by specific NO2 emission sources, and were able to highlight likely atmospheric transport “pathways”. General temporal trends which were also part of our model – weekly, seasonal and linear changes – showed to be in good agreement with previous studies and alternative ways of analysing the time series. Overall, using a non-parametric model provided favorable means for a rapid inspection of this large spatio-temporal NO2 data set, with less bias than parametric approaches, and allowing to visualize dynamical processes of the NO2 distribution at a global scale.
The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can include errors in data, model parameters, or model structure. Dealing with a set of performance measures evaluated at a high temporal resolution implies analyzing and interpreting a high dimensional data set. This paper presents a method for such a hydrological model performance assessment with a high temporal resolution and illustrates its application for two very different rainfall-runoff modeling case studies. The first is the Wilde Weisseritz case study, a headwater catchment in the eastern Ore Mountains, simulated with the conceptual model WaSiM-ETH. The second is the Malalcahuello case study, a headwater catchment in the Chilean Andes, simulated with the physicsbased model Catflow. The proposed time-resolved performance assessment starts with the computation of a large set of classically used performance measures for a moving window. The key of the developed approach is a data-reduction method based on self-organizing maps (SOMs) and cluster analysis to classify the high-dimensional performance matrix. Synthetic peak errors are used to interpret the resulting error classes. The final outcome of the proposed method is a time series of the occurrence of dominant error types. For the two case studies analyzed here, 6 such error types have been identified. They show clear temporal patterns, which can lead to the identification of model structural errors.
Annotationen
(2009)