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"Nicht-Ereignisse", Lebensenttäuschungen aufgrund des dauerhaften Ausbleibens erwünschter Ereignisse oder des Nicht-Erreichens von bedeutsamen Lebenszielen, können zu existenziellen Krisen führen. Die Autoren haben 40 Personen befragt und an ihrem Beispiel die Bewältigungsprozesse solcher Krisen untersucht, die z.B. durch ungewollte Kinderlosigkeit oder eine ausgebliebene berufliche Karriere ausgelöst worden waren. Dabei fanden sie verschiedene Prozesshilfen: kognitive und emotionale Verarbeitungsprozesse, soziale Unterstützung, Ersatzaktivitäten und pragmatisches Handeln. Alle Befragten berichteten von Entwicklungsgewinnen aufgrund der Krise und ihrer Bewältigung.
Die Zunahme an Gewalttaten, insbesondere durch Kinder und Jugendliche, wird in der öffentlichen und pädagogischen Diskussion weithin beklagt. Zwar zeigen zeitvergleichende Analysen, dass von einer dramatischen Erhöhung der Gewalhandlungen keine Rede sein kann; eher ist die öffentliche Sensibilität für derartige Vorfälle gestiegen. Andererseits gibt es erschreckende Beispiele für besonders brutale Übergriffe, die im öffentlichen Bewusstsein naturgemäß dominieren. Eindeutig zugenommen haben in den letzten Jahren politisch motivierte Gewalttaten, insbesondere mit rechtsextremistischem Hintergrund. Doch unabhängig davon, ob und wo die Zahl der Gewalthandlungen angestiegen ist, beinhaltet jede einzelne Tat einen Angriff auf die Menschenwürde und die politische Kultur und ruft deshalb nach Gegenmaßnahmen.
Temporal changes in the occurrence of extreme events in time series of observed precipitation are investigated. The analysis is based on a European gridded data set and a German station-based data set of recent monthly totals (1896=1899–1995=1998). Two approaches are used. First, values above certain defined thresholds are counted for the first and second halves of the observation period. In the second step time series components, such as trends, are removed to obtain a deeper insight into the causes of the observed changes. As an example, this technique is applied to the time series of the German station Eppenrod. It arises that most of the events concern extreme wet months whose frequency has significantly increased in winter. Whereas on the European scale the other seasons also show this increase, especially in autumn, in Germany an insignificant decrease in the summer and autumn seasons is found. Moreover it is demonstrated that the increase of extreme wet months is reflected in a systematic increase in the variance and the Weibull probability density function parameters, respectively.
The climate system can be regarded as a dynamic nonlinear system. Thus, traditional linear statistical methods fail to model the nonlinearities of such a system. These nonlinearities render it necessary to find alternative statistical techniques. Since artificial neural network models (NNM) represent such a nonlinear statistical method their use in analyzing the climate system has been studied for a couple of years now. Most authors use the standard Backpropagation Network (BPN) for their investigations, although this specific model architecture carries a certain risk of over-/underfitting. Here we use the so called Cauchy Machine (CM) with an implemented Fast Simulated Annealing schedule (FSA) (Szu, 1986) for the purpose of attributing and detecting anthropogenic climate change instead. Under certain conditions the CM-FSA guarantees to find the global minimum of a yet undefined cost function (Geman and Geman, 1986). In addition to potential anthropogenic influences on climate (greenhouse gases (GHG), sulphur dioxide (SO2)) natural influences on near surface air temperature (variations of solar activity, explosive volcanism and the El Nino = Southern Oscillation phenomenon) serve as model inputs. The simulations are carried out on different spatial scales: global and area weighted averages. In addition, a multiple linear regression analysis serves as a linear reference. It is shown that the adaptive nonlinear CM-FSA algorithm captures the dynamics of the climate system to a great extent. However, free parameters of this specific network architecture have to be optimized subjectively. The quality of the simulations obtained by the CM-FSA algorithm exceeds the results of a multiple linear regression model; the simulation quality on the global scale amounts up to 81% explained variance. Furthermore the combined anthropogenic effect corresponds to the observed increase in temperature Jones et al. (1994), updated by Jones (1999a), for the examined period 1856–1998 on all investigated scales. In accordance to recent findings of physical climate models, the CM-FSA succeeds with the detection of anthropogenic induced climate change on a high significance level. Thus, the CMFSA algorithm can be regarded as a suitable nonlinear statistical tool for modeling and diagnosing the climate system.
Observed global and European spatiotemporal related fields of surface air temperature, mean-sea-level pressure and precipitation are analyzed statistically with respect to their response to external forcing factors such as anthropogenic greenhouse gases, anthropogenic sulfate aerosol, solar variations and explosive volcanism, and known internal climate mechanisms such as the El Niño-Southern Oscillation (ENSO) and the North Atlantic Oscillation (NAO). As a first step, a principal component analysis (PCA) is applied to the observed spatiotemporal related fields to obtain spatial patterns with linear independent temporal structure. In a second step, the time series of each of the spatial patterns is subject to a stepwise regression analysis in order to separate it into signals of the external forcing factors and internal climate mechanisms as listed above as well as the residuals. Finally a back-transformation leads to the spatiotemporally related patterns of all these signals being intercompared. Two kinds of significance tests are applied to the anthropogenic signals. First, it is tested whether the anthropogenic signal is significant compared with the complete residual variance including natural variability. This test answers the question whether a significant anthropogenic climate change is visible in the observed data. As a second test the anthropogenic signal is tested with respect to the climate noise component only. This test answers the question whether the anthropogenic signal is significant among others in the observed data. Using both tests, regions can be specified where the anthropogenic influence is visible (second test) and regions where the anthropogenic influence has already significantly changed climate (first test).
Der Magnetstein - Wozu braucht es Materialien zum Sachunterricht : Ein Gespräch mit Horst Rumpf
(2003)
Dem Leser einer Reihe von Veröffentlichungen zur Didaktik des Sachunterrichts fällt auf, dass es bei aller Vielzahl von Differenzen und Differenzierungen zu didaktischen und pädagogischen Fragen so etwas wie eine - mehr implizite als explizite - Übereinstimmung in der Konstitution des Gegenstandes "Sache" zu geben scheint. Die "Sache" ist danach das zu Erkennende; der Sachunterricht soll entsprechend den Schüler in die Lage versetzen, zu erkennen, was gegeben ist. Aus einer jüngeren erkenntnistheoretischen Sicht lässt sich die Haltbarkeit dieser Grundannahme bezweifeln. Im Durchgang durch einige Konzepte zur Didaktik des Sachunterrichts soll dieser Zweifel begründet werden.
First results on the production of Xi- and Anti-xi hyperons in Pb+Pb interactions at 40 A GeV are presented. The Anti-xi/Xi- ratio at midrapidity is studied as a function of collision centrality. The ratio shows no significant centrality dependence within statistical errors; it ranges from 0.07 to 0.15. The Anti-xi/Xi- ratio for central Pb+Pb collisions increases strongly with the collision energy.