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Examination of a person who has been a victim of a physical or sexual assault may be very important for upcoming legal proceedings. In the context of a clinical forensic examination, physical findings are recorded and biological trace material is gathered and secured. Ideally, all forensic findings are documented in a detailed report combined with photographic documentation, which employs a forensic scale to depict the size of the injuries. However, the integrity of such forensic findings depends particularly on two factors. First, the examination needs to be conducted professionally to ensure that the findings are properly admissible as court evidence. Second, the examination should take place as soon as possible because the opportunity to successfully secure biological samples declines rapidly with time. Access to low-threshold clinical forensic examinations is not evenly provided in all member states of the European Union (EU); in some states, they are not available at all. As part of the JUSTeU! (Juridical standards for clinical forensic examinations of victims of violence in Europe) project, the Ludwig Boltzmann Institute for Clinical Forensic Imaging in Graz, Austria created (in cooperation with its international partner consortium) a questionnaire: the purpose was to collect information about support for victims of physical and/or sexual assault in obtaining a low-threshold clinical forensic examination in various countries of the EU. Our paper provides a summary of the responses and an overview of the current situation concerning provided clinical forensic services. [ABSTRACT FROM AUTHOR]

The availability of predictive models for chemical processes is the basic prerequisite for offline process optimization. In cases where a predictive model is missing for a process unit within a larger process flowsheet, measured operating data of the process can be used to set up such models combining physical knowledge and process data. In this contribution, the creation and integration of such gray‐box models within the framework of a flowsheet simulator is presented. Results of optimization using different gray‐box models are shown for a virtual cumene process. This work describes the implementation of a framework to support the setup of gray‐box models for flowsheets of chemical production plants. This framework is integrated into a flowsheet simulator enabling optimization of combined rigorous and data‐driven models. [ABSTRACT FROM AUTHOR]