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According to the German penal code, offenders can basically be sanctioned to a prison sentence or (in cases of misdemeanours) to a fine. If an offender is sentenced to a fine, but is not able or willing to make the payment, then the German state can administer a custodial sentence as a replacement. This is called an “Ersatzfreiheitsstrafe” (EFS). The proportion of EFS prisoners accounts for 10% of the German prison population and thus appears to be strikingly high considering the consequences of an imprisonment for the detainee. It has been considered that this is due to high levels of mental disorders in the population of EFS prisoners. This article thus aims at delineating the prevalence of mental disorders in EFS prisoners according to socio‐demographic data and ICD‐10 diagnoses of two recent German studies. Results of these studies indicate that EFS prisoners indeed are for the most part socially and economically deprived and show a high prevalence of mental disorders. It is argued that their resulting lack of social competence may lead to incapability of avoiding their fee being converted into a prison sentence. As a consequence EFSs have to be seen as supporting social stigmatization and risking a further exclusion from society.

Presents a new qualitative fault tree evaluation algorithm based on bit manipulation techniques for the identification of the largest independent sub‐trees and the subsequent determination of all minimal cut sets of large and complex fault trees. The methodology developed is validated by direct application to a complex fault tree taken from the literature. Results obtained are compared with those available in the literature. Shows that the use of the algorithm (FTABMT) developed results in significant savings in both computer time and storage requirements.