Inverting the lives of 'others': retelling the Nazi past in 'Ehe im Schatten' and 'Das Leben der Anderen'

The article compares Florian Henckel von Donnersmarck's film Das Leben der Anderen (2006) with Kurt Maetzig's early post-war film Ehe im Schatten (1947). The comparison is based on significant narrative and thematic elements which the films share: They both have a ‘theatre couple’, representatives of the ‘Bildungsbürgertum’, at the centre of the story; in both cases the couple faces a crisis caused by the first and second German dictatorship respectively and then both try to solve the crisis by relying on the classical ‘bürgerliches Erbe’, particularly the ‘bürgerliches Trauerspiel’. The extensive use of the ‘bürgerliches Erbe’ in the films activates the function this heritage had for the definition of the German nation in the nineteenth century. However, while Maetzig's film shows how the ‘heritage’ and its representatives fail in the face of National Socialism, von Donnersmarck's film claims the effectiveness of this ‘heritage’ in the fight against the East German dictatorship. Von Donnersmarck thus inverts a critical film tradition of which Ehe im Schatten is an example; furthermore, as this tradition emerged from dealing with the Third Reich, von Donnersmarck's film, it will be argued, is more interested in the redemption of the Nazi past than the East German past.

GSHMC: an efficient method for molecular simulation

The hybrid Monte Carlo (HMC) method is a popular and rigorous method for sampling from a canonical ensemble. The HMC method is based on classical molecular dynamics simulations combined with a Metropolis acceptance criterion and a momentum resampling step. While the HMC method completely resamples the momentum after each Monte Carlo step, the generalized hybrid Monte Carlo (GHMC) method can be implemented with a partial momentum refreshment step. This property seems desirable for keeping some of the dynamic information throughout the sampling process similar to stochastic Langevin and Brownian dynamics simulations. It is, however, ultimate to the success of the GHMC method that the rejection rate in the molecular dynamics part is kept at a minimum. Otherwise an undesirable Zitterbewegung in the Monte Carlo samples is observed. In this paper, we describe a method to achieve very low rejection rates by using a modified energy, which is preserved to high-order along molecular dynamics trajectories. The modified energy is based on backward error results for symplectic time-stepping methods. The proposed generalized shadow hybrid Monte Carlo (GSHMC) method is applicable to NVT as well as NPT ensemble simulations.

A Gaussian-mixture ensemble transform filter

We generalize the popular ensemble Kalman filter to an ensemble transform filter, in which the prior distribution can take the form of a Gaussian mixture or a Gaussian kernel density estimator. The design of the filter is based on a continuous formulation of the Bayesian filter analysis step. We call the new filter algorithm the ensemble Gaussian-mixture filter (EGMF). The EGMF is implemented for three simple test problems (Brownian dynamics in one dimension, Langevin dynamics in two dimensions and the three-dimensional Lorenz-63 model). It is demonstrated that the EGMF is capable of tracking systems with non-Gaussian uni- and multimodal ensemble distributions. Copyright © 2011 Royal Meteorological Society

A dynamical systems framework for intermittent data assimilation

We consider the problem of discrete time filtering (intermittent data assimilation) for differential equation models and discuss methods for its numerical approximation. The focus is on methods based on ensemble/particle techniques and on the ensemble Kalman filter technique in particular. We summarize as well as extend recent work on continuous ensemble Kalman filter formulations, which provide a concise dynamical systems formulation of the combined dynamics-assimilation problem. Possible extensions to fully nonlinear ensemble/particle based filters are also outlined using the framework of optimal transportation theory.

A nonparametric ensemble transform method for Bayesian inference

Many applications, such as intermittent data assimilation, lead to a recursive application of Bayesian inference within a Monte Carlo context. Popular data assimilation algorithms include sequential Monte Carlo methods and ensemble Kalman filters (EnKFs). These methods differ in the way Bayesian inference is implemented. Sequential Monte Carlo methods rely on importance sampling combined with a resampling step, while EnKFs utilize a linear transformation of Monte Carlo samples based on the classic Kalman filter. While EnKFs have proven to be quite robust even for small ensemble sizes, they are not consistent since their derivation relies on a linear regression ansatz. In this paper, we propose another transform method, which does not rely on any a priori assumptions on the underlying prior and posterior distributions. The new method is based on solving an optimal transportation problem for discrete random variables. © 2013, Society for Industrial and Applied Mathematics

TRY: a global database of plant traits

Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

Ensemble transform Kalman-Bucy filters

Two recent works have adapted the Kalman–Bucy filter into an ensemble setting. In the first formulation, the ensemble of perturbations is updated by the solution of an ordinary differential equation (ODE) in pseudo-time, while the mean is updated as in the standard Kalman filter. In the second formulation, the full ensemble is updated in the analysis step as the solution of single set of ODEs in pseudo-time. Neither requires matrix inversions except for the frequently diagonal observation error covariance. We analyse the behaviour of the ODEs involved in these formulations. We demonstrate that they stiffen for large magnitudes of the ratio of background error to observational error variance, and that using the integration scheme proposed in both formulations can lead to failure. A numerical integration scheme that is both stable and is not computationally expensive is proposed. We develop transform-based alternatives for these Bucy-type approaches so that the integrations are computed in ensemble space where the variables are weights (of dimension equal to the ensemble size) rather than model variables. Finally, the performance of our ensemble transform Kalman–Bucy implementations is evaluated using three models: the 3-variable Lorenz 1963 model, the 40-variable Lorenz 1996 model, and a medium complexity atmospheric general circulation model known as SPEEDY. The results from all three models are encouraging and warrant further exploration of these assimilation techniques.

Anti-Slavic imagery in German radical nationalist discourse at the turn of the twentieth century: a prelude to Nazi ideology?

By applying methods of cognitive metaphor theory, Jaworska examines metaphorical scenarios employed in the discourse of anti-Slavism, which featured prominently in radical nationalist propaganda in Germany at the turn of the twentieth century. She does so by analysing metaphorical expressions used to refer to the Polish population living in the eastern provinces of Prussia, in the so-called Ostmark. Her article is based on an analysis of a range of pamphlets and newspaper articles written by some of the leading figures of two nationalist organizations: the Pan-German League (Alldeutscher Verband) and the Eastern Marches Society(Ostmarkenverein). The main research questions it addresses are: What kind of metaphoric scenarios were used to depict the Polish minority, and to what extent were the metaphorical patterns of anti-Slavic imagery similar to those employed in the antisemitic propaganda of the Nazi era? Is there a discursive continuity between the radical nationalism of imperial Germany and the National Socialism of the Third Reich at the level of metaphorical scenarios? Ultimately, Jaworska attempts to contribute to a better understanding of the cognitive mechanisms underlying radical and essentially racist attitudes.

The fractured lives of German Bohemian children, born 1933-40 in the area known as Sudetenland: a memory study, Nablonz-Neugablonz

At the Paris Peace Conferences of 1918-1919, new states aspiring to be nation-states were created for 60 million people, but at the same time 25 million people found themselves as ethnic minorities. This change of the old order in Europe had a considerable impact on one such group, more than 3 million Bohemian German-speakers, later referred to as Sudeten Germans. After the demise of the Habsburg Empire In 1918, they became part of the new state of Czechoslovakia. In 1938, the Munich Agreement – prelude to the Second World War – integrated them into Hitler’s Reich; in 1945-1946 they were expelled from the reconstituted state of Czechoslovakia. At the centre of this War Child case study are German children from the Northern Bohemian town and district, formerly known as Gablonz an der Neisse, famous for exquisite glass art, now Jablonec nad Nisou in the Czech Republic. After their expulsion they found new homes in the post-war Federal Republic of Germany. In addition, testimonies have been drawn upon of some Czech eyewitnesses from the same area, who provided their perspective from the other side, as it were. It turned out to be an insightful case study of the fate of these communities, previously studied mainly within the context of the national struggle between Germans and Czechs. The inter-disciplinary research methodology adopted here combines history and sociological research to demonstrate the effect of larger political and social developments on human lives, not shying away from addressing sensitive political and historical issues, as far as these are relevant within the context of the study. The expellees started new lives in what became Neugablonz in post-war Bavaria where they successfully re-established the industries they had had to leave behind in 1945-1946. Part 1 of the study sheds light on the complex Czech-German relationship of this important Central European region, addressing issues of democracy, ethnicity, race, nationalism, geopolitics, economics, human geography and ethnography. It also charts the developments leading to the expulsion of the Sudeten Germans from Czechoslovakia after 1945. What is important in this War Child study is how the expellees remember their history while living as children in Sudetenland and later. The testimony data gained indicate that certain stereotypes often repeated within the context of Sudeten issues such as the confrontational nature of inter-ethnic relations are not reflected in the testimonies of the respondents from Gablonz. In Part 2 the War Child Study explores the memories of the former Sudeten war children using sociological research methods. It focuses on how they remember life in their Bohemian homeland and coped with the life-long effects of displacement after their expulsion. The study maps how they turned adversity into success by showing a remarkable degree of resilience and ingenuity in the face of testing circumstances due to the abrupt break in their lives. The thesis examines the reasons for the relatively positive outcome to respondents’ lives and what transferable lessons can be deduced from the results of this study.