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Bielefeld, Germany

Schulz M.,FH Bielefeld | Gray R.,University of the West of England | Abderhalden C.,University of Bern | Behrens J.,Martin Luther University of Halle Wittenberg
Schizophrenia Research | Year: 2013

Background: Non-adherence with antipsychotic medication is common in patients with schizophrenia. Aims: To establish the efficacy of adherence therapy (AT) compared to treatment as usual (TAU) in improving medication compliance in patients following an acute episode of schizophrenia. Method: The study was designed as a parallel group, single blind, randomised controlled trial. Fieldwork was conducted in four centres (3 in Germany and 1 in Switzerland) and involved a total of 161 patients. Patients received 8 sessions of AT in addition to treatment as usual. The main outcomes of this study were adherence and psychopathology at 12. weeks post discharge follow up. Results: In total 80 patients received AT and 57 TAU. Intention-to-treat analysis included all randomised patients. Psychopathology, as determined using the PANSS-total, improved in the AT compared to TAU group by a mean of - 6.16 points 12. weeks after discharge from hospital (p < .05). AT had no significant effects on patients' adherence, treatment attitudes or functioning. No significant adverse events were reported. Conclusion: AT improves psychopathology in patients recovering from an acute episode of schizophrenia. © 2013 Elsevier B.V. Source

Tamm U.,FH Bielefeld
2014 Information Theory and Applications Workshop, ITA 2014 - Conference Proceedings | Year: 2014

The Lambert W function fulfills W(y)· eW(y) = y. With the choice y = log (x) it can hence be applied to invert the function f (x) = x · log(x), which is of some interest in the problems discussed. Further applications of the Lambert W function in information theory are briefly surveyed. © 2014 IEEE. Source

Thiels C.,FH Bielefeld
British Journal of Psychiatry | Year: 2013

In mid-19th-century Germany the conviction that 'mental disease is brain disease' was accompanied by a call for social reform in psychiatry. During neurology training, future psychiatrists often encounter patients with mental disorders rarely seen in psychiatric departments and learn how to avoid misdiagnosing brain diseases as mental disorders. Source

Tamm U.,FH Bielefeld
2015 Information Theory and Applications Workshop, ITA 2015 - Conference Proceedings | Year: 2015

Integer codes correcting a single error in the maximum metric are considered. This corresponds to a packing of tori by cubes. For an asymmetric error of size one these cubes have side length 2 and the problem can be shown to be equivalent to finding zero-error codes for cycles in the sense of Shannon and Lovasz. For side length greater 3 the equivalence of single error correcting integer codes and zero-error codes does not hold any more. © 2015 IEEE. Source

Pross S.,FH Bielefeld
Journal of integrative bioinformatics | Year: 2011

Biological systems are often very complex so that an appropriate formalism is needed for modeling their behavior. Hybrid Petri Nets, consisting of time-discrete Petri Net elements as well as continuous ones, have proven to be ideal for this task. Therefore, a new Petri Net library was implemented based on the object-oriented modeling language Modelica which allows the modeling of discrete, stochastic and continuous Petri Net elements by differential, algebraic and discrete equations. An appropriate Modelica-tool performs the hybrid simulation with discrete events and the solution of continuous differential equations. A special sub-library contains so-called wrappers for specific reactions to simplify the modeling process. The Modelica-models can be connected to Simulink-models for parameter optimization, sensitivity analysis and stochastic simulation in Matlab. The present paper illustrates the implementation of the Petri Net component models, their usage within the modeling process and the coupling between the Modelica-tool Dymola and Matlab/Simulink. The application is demonstrated by modeling the metabolism of Chinese Hamster Ovary Cells. Source

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