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Based on the metaphor of “liminality” in literary studies, this paper examines two different approaches to the literary genre of travelogues, using the example of Adelbert von Chamisso‟s Voyage Around the World (1836). One approach, with the help of autobiographical research, sheds light on the author-specific key motifs of “omnipotent time” and the process of aging. In the second approach, the focus shifts to the relationship between literature and natural science, i.e. to Chamisso‟s transitional position in the context of the historicization and dynamization of the sciences and humanities in the 19th century. Rather than thinking of “philology” and “cultural studies” as opposing methods, this article thus suggests a more in-tercessory position for the purpose of a fruitful study of travel literature.
This paper examines the well-known practice of developing a conceptual frame-work for reading works of literature in such a way as to illuminate previously ignored aspects of those works. It investigates the nature or genre of such discoveries: Are they philological? Hermeneutic? Do they correspond to the discipline of the framework selected? This problem is considered in the case of an example of the deployment of a very specific philosophical framework, namely the problem of skepticism as glossed by the American philosopher Stanley Cavell. This framework brings to light a structural affinity between two seemingly disparate moments in the history of German lyric poetry: the Biedermeier period and the works of Konkrete Dichtung from the mid-twentieth century. The paper postulates this affinity as an exam-ple of the kind of “discovery” whose type, usefulness, or even existence as discovery might be called into question and perhaps not, ultimately, agreed on.
CONTENTS: Keynote Address and Invited Plenary Lectures Symposia Debates and Panels Oral Presentations and Specific Topics Poster Presentations Workshop Presentations Case Study Presentations and Media Presentations Symposien Workshops
TRENTOOL : an open source toolbox to estimate neural directed interactions with transfer entropy
(2011)
To investigate directed interactions in neural networks we often use Norbert Wiener's famous definition of observational causality. Wiener’s definition states that an improvement of the prediction of the future of a time series X from its own past by the incorporation of information from the past of a second time series Y is seen as an indication of a causal interaction from Y to X. Early implementations of Wiener's principle – such as Granger causality – modelled interacting systems by linear autoregressive processes and the interactions themselves were also assumed to be linear. However, in complex systems – such as the brain – nonlinear behaviour of its parts and nonlinear interactions between them have to be expected. In fact nonlinear power-to-power or phase-to-power interactions between frequencies are reported frequently. To cover all types of non-linear interactions in the brain, and thereby to fully chart the neural networks of interest, it is useful to implement Wiener's principle in a way that is free of a model of the interaction [1]. Indeed, it is possible to reformulate Wiener's principle based on information theoretic quantities to obtain the desired model-freeness. The resulting measure was originally formulated by Schreiber [2] and termed transfer entropy (TE). Shortly after its publication transfer entropy found applications to neurophysiological data. With the introduction of new, data efficient estimators (e.g. [3]) TE has experienced a rapid surge of interest (e.g. [4]). Applications of TE in neuroscience range from recordings in cultured neuronal populations to functional magnetic resonanace imaging (fMRI) signals. Despite widespread interest in TE, no publicly available toolbox exists that guides the user through the difficulties of this powerful technique. TRENTOOL (the TRansfer ENtropy TOOLbox) fills this gap for the neurosciences by bundling data efficient estimation algorithms with the necessary parameter estimation routines and nonparametric statistical testing procedures for comparison to surrogate data or between experimental conditions. TRENTOOL is an open source MATLAB toolbox based on the Fieldtrip data format. ...
Over the past two decades the “one drug – one target – one disease” concept became the prevalent paradigm in drug discovery. The main idea of this approach is the identification of a single protein target whose inhibition leads to a successful treatment of the examined disease. The predominant assumption is that highly selective ligands would avoid unwanted side effects caused by binding to secondary non-therapeutic targets. In recent years the results of post-genomic and network biology showed that proteins rarely act in isolated systems but rather as a part of a highly connected network [1]. In addition this connectivity leads to more robust systems that cannot be interfered by the inhibition of a single target of that network and consequently might not lead to the desired therapeutic effect [2]. Furthermore studies prove that robust systems are rather affected by weak inhibitions of several parts than by a complete inhibition of a single selected element of that system [3]. Therefore there is an increasing interest in developing drugs that take effect on multiple targets simultaneously but is concurrently a great challenge for medicinal chemists. There has to be a sufficient activity on each target as well as an adequate pharmacokinetic profile [4]. Early design strategies tried to link the pharmacophors of known inhibitors, however these methods often lead to high molecular weight and low ligand efficacy. We present a new rational approach based on a retrosynthetic combinatorial analysis procedure [5] on approved ligands of multiple targets. These RECAP fragments are used to design a large combinatorial library containing molecules featuring chemical properties of each ligand class. The molecules are further validated by machine learning models, like random forests and self-organizing maps, regarding their activity on the targets of interest.