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With a steady increase of regulatory requirements for business processes, automation support of compliance management is a field garnering increasing attention in Information Systems research. Several approaches have been developed to support compliance checking of process models. One major challenge for such approaches is their ability to handle different modeling techniques and compliance rules in order to enable widespread adoption and application. Applying a structured literature search strategy, we reflect and discuss compliance-checking approaches in order to provide an insight into their generalizability and evaluation. The results imply that current approaches mainly focus on special modeling techniques and/or a restricted set of types of compliance rules. Most approaches abstain from real-world evaluation which raises the question of their practical applicability. Referring to the search results, we propose a roadmap for further research in model-based business process compliance checking.
Assessment of RF Safety of Transmit Coils at 7 Tesla by Experimental and Numerical Procedures (490.)
(2012)
In this study we observed courses of micturition symptoms and differentiated degrees of symptoms for each point in time while also considering the impact of bothersomeness. Our data show that not only significantly more patients who have undergone BT suffer from OAB than those who have undergone RP, but also that those affected show significantly higher values for severity of OAB symptoms throughout the whole observation period of 36 months. Our data analysis further shows that variability of OAB symptoms as well as fluctuation of severity of OAB symptoms vary to a significantly higher degree after BT than after RP. Looking only at mean figures at a given point in time clearly underestimates the underlying problem. This fact is not reflected in the literature.
Cell-based sensors for the detection of gases have long been underrepresented, due to the cellular requirement of being cultured in a liquid environment. In this work we established a cell-based gas biosensor for the detection of toxic substances in air, by adapting a commercial sensor chip (Bionas®), previously used for the measurement of pollutants in liquids. Cells of the respiratory tract (A549, RPMI 2650, V79), which survive at a gas phase in a natural context, are used as biological receptors. The physiological cell parameters acidification, respiration and morphology are continuously monitored in parallel. Ammonia was used as a highly water-soluble model gas to test the feasibility of the sensor system. Infrared measurements confirmed the sufficiency of the medium draining method. This sensor system provides a basis for many sensor applications such as environmental monitoring, building technology and public security.