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The concept of an injective affine embedding of the quantum states into a set of classical states, i.e., into the set of the probability measures on some measurable space, as well as its relation to statistically complete observables is revisited, and its limitation in view of a classical reformulation of the statistical scheme of quantum mechanics is discussed. In particular, on the basis of a theorem concerning a non-denseness property of a set of coexistent effects, it is shown that an injective classical embedding of the quantum states cannot be supplemented by an at least approximate classical description of the quantum mechanical effects. As an alternative approach, the concept of quasi-probability representations of quantum mechanics is considered.
Network theory provides novel concepts that promise an improved characterization of interacting dynamical systems. Within this framework, evolving networks can be considered as being composed of nodes, representing systems, and of time-varying edges, representing interactions between these systems. This approach is highly attractive to further our understanding of the physiological and pathophysiological dynamics in human brain networks. Indeed, there is growing evidence that the epileptic process can be regarded as a large-scale network phenomenon. We here review methodologies for inferring networks from empirical time series and for a characterization of these evolving networks. We summarize recent findings derived from studies that investigate human epileptic brain networks evolving on timescales ranging from few seconds to weeks. We point to possible pitfalls and open issues, and discuss future perspectives.
The scope of this study is the measurement of endotoxin adsorption rate for carbonized rice husk. It showed good adsorption properties for LPS. During the batch experiments, several techniques were used and optimized for improving the material’s adsorption behavior. Also, with the results obtained it was possible to differentiate the materials according to their adsorption capacity and kinetic characteristics.
Among the variety of transducer concepts proposed for label-free detection of biomolecules, the semiconductor field-effect device (FED) is one of the most attractive platforms. As medical techniques continue to progress towards diagnostic and therapies based on biomarkers, the ability of FEDs for a label-free, fast and real-time detection of multiple pathogenic and physiologically relevant molecules with high specificity and sensitivity offers very promising prospects for their application in point-of-care and personalized medicine for an early diagnosis and treatment of diseases. The presented paper reviews recent advances and current trends in research and development of different FEDs for label-free, direct electrical detection of charged biomolecules by their intrinsic molecular charge. The authors are mainly focusing on the detection of the DNA hybridization event, antibody-antigen affinity reaction as well as clinically relevant biomolecules such as cardiac and cancer biomarkers.
In this work, the catalyst manganese(IV) oxide (MnO2), of calorimetric gas sensors (to monitor the sterilization agent vaporized hydrogen peroxide) has been investigated in more detail. Chemical analyses by means of X-ray-induced photoelectron spectroscopy have been performed to unravel the surface chemistry prior and after exposure to hydrogen peroxide vapor at elevated temperature, as applied in the sterilization processes of beverage cartons. The surface characterization reveals a change in oxidation states of the metal oxide catalyst after exposure to hydrogen peroxide. Additionally, a cleaning effect of the catalyst, which itself is attached to the sensor surface by means of a polymer interlayer, could be observed.