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Molecular rods consisting of a hydrophobic backbone and terminally varying functional groups have been synthesized for applications for the functionalization of membranes. In the present study, we employ a spin-labeled analogue of a recently described new class of molecular rods to characterize their dynamic interactions with membranes. By using the different approaches of ESR and NMR spectroscopy, we show that the spin moiety of the membrane-embedded spin-labeled rod is localized in the upper chain/glycerol region of membranes of different compositions. The rod is embedded within the membrane in a tilted orientation to adjust for the varying hydrophobic thicknesses of these bilayers. This orientation does not perturb the membrane structure. The water solubility of the rod is increased significantly in the presence of certain cyclodextrins. These cyclodextrins also allow the rods to be extracted from the membrane and incorporated into preformed membranes. The latter will improve the future applications of these rods in cellular systems as stable membrane-associated anchors for the functionalization of membrane surfaces.
The development of self-adaptive software requires the engineering of an adaptation engine that controls the underlying adaptable software by feedback loops. The engine often describes the adaptation by runtime models representing the adaptable software and by activities such as analysis and planning that use these models. To systematically address the interplay between runtime models and adaptation activities, runtime megamodels have been proposed. A runtime megamodel is a specific model capturing runtime models and adaptation activities. In this article, we go one step further and present an executable modeling language for ExecUtable RuntimE MegAmodels (EUREMA) that eases the development of adaptation engines by following a model-driven engineering approach. We provide a domain-specific modeling language and a runtime interpreter for adaptation engines, in particular feedback loops. Megamodels are kept alive at runtime and by interpreting them, they are directly executed to run feedback loops. Additionally, they can be dynamically adjusted to adapt feedback loops. Thus, EUREMA supports development by making feedback loops explicit at a higher level of abstraction and it enables solutions where multiple feedback loops interact or operate on top of each other and self-adaptation co-exists with offline adaptation for evolution.
Fluorescent carbon nanodots (CNDs) are very promising nanomaterials for a broad range of applications because of their high photostability, presumed selective luminescence, and low cost at which they can be produced. In this respect, CNDs are superior to well-established semiconductor quantum dots and organic dyes. However, reported synthesis protocols for CNDs typically lead to low photoluminescence quantum yield (PLQY) and low reproducibility, resulting in a poor understanding of the CND chemistry and photophysics. Here, we report a one-step synthesis of nitrogen-doped carbon nanodots (N-CNDs) from various carboxylic acids, Tris, and ethylenediaminetetraacetic acid resulting in high PLQY of up to 90%. The reaction conditions in terms of starting materials, temperature, and reaction time are carefully optimized and their influence on the photophysical properties is characterized. We find that citric acid-derived N-CNDs can result in a very high PLQY of 90%, but they do not show selective luminescence. By contrast, acetic acid-derived N-CNDs show selective luminescence but a PLQY of 50%. The chemical composition of the surface and core of these two selected N-CND types is characterized among others by high-resolution synchrotron X-ray photoelectron spectroscopy using single isolated N-CND clusters. The results indicate that photoexcitation occurs in the N-CND core, whereas the emission properties are determined by the N-CND surface groups.
In der derzeitigen Wahrnehmung werden die Sommer dürrer, heißer und extremer – dieser Eindruck verstärkt sich im urbanen Raum durch das Auftreten von Hitzeinseleffekten in dicht bebauten Gebieten. Um das wirkliche Ausmaß der Dürre bewerten zu können, wurden Zeitreihendaten von 31 urbanen Klimastationen (DWD) für den Zeitraum 1950 bis 2019 mittels des standardisierten Niederschlagsindex (SPI) bezüglich Dürrelängen, Dürreextrema, Hitzewellen und gleichzeitig auftretenden Hitze- und Dürremonaten ausgewertet.
Die Analyse zeigt eine große Heterogenität innerhalb von Deutschland: In den meisten Städten trat 2018 eine lange Dürre von einer durchschnittlichen Dauer von 6 Monaten auf, gleichzeitig gehörte das Jahr 2018 nur bei einem Drittel der Städte zu den drei Jahren mit den längsten Dürren seit 1950. Bei den meisten betrachteten Stationen traten die längsten Dürren in den Jahren 1953, 1971 und 1976 auf. Bei einigen südlichen und mitteldeutschen Städten kann man eine statistisch signifikante Zunahme der Anzahl der Dürremonate pro Dekade seit 1950 verzeichnen. Andere Städte, eher im Norden und Nordwesten gelegen, zeigen nur in den letzten zwei Dekaden eine Zunahme oder gar keinen Trend. Die Compoundanalyse von gleichzeitig auftretenden Hitze- und Dürremonaten zeigt bei den meisten Stationen eine starke Zunahme innerhalb der letzten zwei Dekaden, wobei die beiden Komponenten regional mit einem sehr unterschiedlichen Anteil zur Zunahme der Compoundereignisse beitragen.
This article presents several acceptability rating experiments concerned with crossing wh-movement in German multiple questions. Our results show that there is no general superiority effect in German, thus refuting claims to the contrary by Featherston (2005). However, acceptability is reduced when a wh-phrase crosses a wh-subject with which it agrees in animacy. We explain this finding in terms of the availability of different sorting keys for the answers to the multiple questions.
Improving scalability and reward of utility-driven self-healing for large dynamic architectures
(2020)
Self-adaptation can be realized in various ways. Rule-based approaches prescribe the adaptation to be executed if the system or environment satisfies certain conditions. They result in scalable solutions but often with merely satisfying adaptation decisions. In contrast, utility-driven approaches determine optimal decisions by using an often costly optimization, which typically does not scale for large problems. We propose a rule-based and utility-driven adaptation scheme that achieves the benefits of both directions such that the adaptation decisions are optimal, whereas the computation scales by avoiding an expensive optimization. We use this adaptation scheme for architecture-based self-healing of large software systems. For this purpose, we define the utility for large dynamic architectures of such systems based on patterns that define issues the self-healing must address. Moreover, we use pattern-based adaptation rules to resolve these issues. Using a pattern-based scheme to define the utility and adaptation rules allows us to compute the impact of each rule application on the overall utility and to realize an incremental and efficient utility-driven self-healing. In addition to formally analyzing the computational effort and optimality of the proposed scheme, we thoroughly demonstrate its scalability and optimality in terms of reward in comparative experiments with a static rule-based approach as a baseline and a utility-driven approach using a constraint solver. These experiments are based on different failure profiles derived from real-world failure logs. We also investigate the impact of different failure profile characteristics on the scalability and reward to evaluate the robustness of the different approaches.
Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate.