Erschöpfte Literatur. Über das Neue bei Samuel Beckett

Exhausted Literature. The Emergence of the New in Samuel Beckett's Novels and Plays. The article investigates literary subjectivity in some texts by Samuel Beckett. The article proceeds by relating the ways of how narration and speech acts constitute literary subjectivity to the problems of subjectivity that scientific investigations deal with. While successful self‐regulation of the organism nourishes the roots of subjectivity, i. e. the habits, subjectivity decomposes in states of exhaustion, when self‐regulation breaks down. As soon as a certain threshold is transgressed, fatigue sets in, alters the personality and eventually leads to exhaustion – a state, which psychiatrists compare to mental illness. Notwithstanding the different explanations given, scientists agreed about the effects of exhaustion. According to their investigations, the decomposition of personality by exhaustion generally does not involve apathy, withdrawal from activity or termination of movements, but rather mere action. Similarly, in Beckett's novels and plays exhaustion is much more than tiredness, as French philosopher Gilles Deleuze observed. For Beckett, exhaustion is rather the model for both literary innovation and a new concept of subjectivity, which he explores on the basis of a detailed knowledge of physiology, psychology, and psychiatry, but using his own literary means. The exhausted subject is beyond any calculus of activity. It will perform an activity even if he or she makes mistakes or loses control, and will thus act in an unpredictable way. This unpredictable action is not an exception in the continuation of the habits, but rather points to the moment when a new subjectivity emerges. Such new subjectivity surfaces in Beckett's novels and plays in forms of literary innovation.     

Aus Österreich emigrierte Sozialwissenschaftler. Überblick und Stand der Forschung

The article presents an general view over the enforced migration of Austrian social scientists after 1933. The author argues that the Austrian case is a specific one: first in consequence of the two successive dictatorships, second because of the devastating consequences of the emigration movement for the Austrian scientific community and culture. Only a few of the refugees returned to Austria after 1945. Further could be demonstrated that the Austrian refugees were quickly promoted in the scientific world of their exile countries, by way of comparison — especially in the United States.     

A Hybrid Framework for Space–Time Modeling of Environmental Data. 环境数据时空建模的混合框架

The space–time autoregressive integrated moving average (STARIMA) model family provides useful tools for modeling space–time processes that exhibit stationarity (or near stationarity) in space and time. However, a more general method for routine use and efficient computation is needed to model the nonlinearities and nonstationarities of environmental space–time series. This article presents a hybrid framework combining machine learning and statistical methods to address this issue. It uses an artificial neural network (ANN) to extract global deterministic (nonlinear) space–time trends and a STARIMA model to extract local stochastic space–time variations in data. A four‐stage procedure is proposed for analyzing and modeling space–time series. The proposed framework and procedures are applied to forecast annual average temperature at 137 national meteorological stations in China. The results demonstrate that the hybrid framework achieves better forecasting accuracy than the STARIMA model alone. This finding suggests that the combination of machine learning and statistical methods provides a very powerful tool for analyzing and modeling space–time series of environmental data that have strong spatial nonlinear and nonstationary components.