Alcohol representations are socially situated: an investigation of beverage representations by using a property generation task

Previous research suggests that people's representations of alcoholic beverages play an important role in drinking behavior. However, relatively little is known about the contents of these representations. Here, we introduce the property generation task as a tool to explore these representations in detail. In a laboratory study (N = 110), and a bar field-study (N = 56), participants listed typical properties of alcoholic beverages, sugary beverages, and water. Each of these properties was then categorized using a previously developed, hierarchical coding scheme. For example, the property “sweet” was categorized as referring to “taste”, which falls under “sensory experience”, which falls under “consumption situation”. Afterwards, participants completed measures of drinking behavior and alcohol craving. Results showed that alcoholic beverages were strongly represented in terms of consumption situations, with 57% and 69% of properties relating to consumption in the laboratory and the bar study, respectively. Specifically, alcoholic beverages were more strongly represented in terms of the social context of consumption (e.g., “with friends”) than the other beverages. In addition, alcoholic beverages were strongly represented in terms of sensory experiences (e.g. “sweet”) and positive outcomes (e.g. “creates fun”), as were the sugary beverages and water. In Study 1, the extent to which alcoholic beverages were represented in terms of social context was positively associated with craving and regularly consuming alcohol. The property generation task provides a useful tool to access people's idiosyncratic representations of alcoholic beverages. This may further our understanding of drinking behavior, and help to tailor research and interventions to reduce drinking of alcoholic and other high-calorie beverages

Investigations on alternative substances for control of apple scab - results from sanitation trials

The intention of this research project, which was supported within the "Bundesprogramm Ökologischer Landbau", was to look for alternatives in organic fruit growing to control apple scab, Venturia inaequalis. One important part of the investigations was the application of different substances like microbiological nutrient media, enzymes usually used for production of fruit juices and organic fertilizers on their effect on the ascospore potential on depots of fallen leaves. Some substances like TRYPTIC SOY BROTH increased the decomposition of the leaves significantly, other like BACTOFIL B and HUMOFIX showed nearly no effect on the decomposition, but reduced the ascospore potential in early spring by 80 % compared to the untreated control

Universality of weakly bound dimers and Efimov trimers close to Li-Cs Feshbach resonances

We study the interspecies scattering properties of ultracold Li-Cs mixtures in their two energetically lowest spin channels in the magnetic field range between 800 G and 1000 G. Close to two broad Feshbach resonances we create weakly bound LiCs dimers by radio-frequency association and measure the dependence of the binding energy on the external magnetic field strength. Based on the binding energies and complementary atom loss spectroscopy of three other Li-Cs s-wave Feshbach resonances we construct precise molecular singlet and triplet electronic ground state potentials using a coupled-channels calculation. We extract the Li-Cs interspecies scattering length as a function of the external field and obtain almost a ten-fold improvement in the precision of the values for the pole positions and widths of the s-wave Li-Cs Feshbach resonances as compared to our previous work [Pires \textit{et al.}, Phys. Rev. Lett. \textbf{112}, 250404 (2014)]. We discuss implications on the Efimov scenario and the universal geometric scaling for LiCsCs trimers

Universal three-body recombination and Efimov resonances in an ultracold Li-Cs mixture

We study Efimov resonances via three-body loss in an ultracold two-component gas of fermionic $^6$Li and bosonic $^{133}$Cs atoms close to a Feshbach resonance at 843~G, extending results reported previously [Pires \textit{et al.}, Phys. Rev. Lett. 112, 250404 (2014)] to temperatures around 120~nK. The experimental scheme for reaching lower temperatures is based upon compensating the gravity-induced spatial separation of the mass-imbalanced gases with bichromatic optical dipole traps. We observe the first and second excited Li-Cs-Cs Efimov resonance in the magnetic field dependence of the three-body event rate constant, in good agreement with the universal zero-range theory at finite temperature [Petrov and Werner, Phys. Rev. A 92, 022704 (2015)]. Deviations are found for the Efimov ground state, and the inelasticity parameter $\eta$ is found to be significantly larger than those for single-species systems

Recovering the mass and the charge of a Reissner-Nordstr\"om black hole by an inverse scattering experiment

In this paper, we study inverse scattering of massless Dirac fields that propagate in the exterior region of a Reissner-Nordstr\"om black hole. Using a stationary approach we determine precisely the leading terms of the high-energy asymptotic expansion of the scattering matrix that, in turn, permit us to recover uniquely the mass of the black hole and its charge up to a sign

A data-driven approach for quality analytics of screwing processes in a global learning factory

Quality problems of screwing processes in assembly systems, which are an important issue for operation excellence, needs to be quickly analyzed and solved. A network can be very beneficial for root cause analysis due to different data from various factories. Nevertheless, it is difficult to obtain reliable and consistent data. In this context, this paper aims to develop a method for data-driven oriented quality analytics of screwing processes considering a global production network. Firstly, the overview of data structure is introduced. Further, the data transformation is modelled for edge- and cloud-based analytics across the global production network. Lastly, the rules for analyzing are identified. A joint case study based on Learning Factory Global Production (LF) in Germany and I4.0 Innovation Centre and Artificial Intelligence Innovation Factory (IC&AIIF) in China is used to validate the proposed approach, which is also a new teaching method for quality analysis in the framework of learning factory