Globular cluster studies suggest that a signature in the spectra of RGB stars in a globular cluster are anti-correlations in Mg-Al and Na-O. In this work, a small sample of 12 RGB stars of the globular cluster M30 is investigated using VLT-UVES high-resolution spectrograph. I use photometric stellar parameters to derive the abundances of Fe, Na, Al and Mg in SIU – a visual spectral analysis tool using 1-dimensional hydrostatic plane parallel MAFAGS atmospheres assuming mixing length convection and treating line formation in LTE. We found signatures of Mg-Al anti-correlation in M30 with the majority of the stars belonging to the intermediate polluted group. Oxygen couldn’t be measured but an indirect clue to the Na-O anti-correlation is found due to the direct correlation of Al-Na. These results are consistent with recent studies of other globular clusters.

Using a probabilistic approach for exploring latent patterns in high-dimensional co-occurrence data, topic models offer researchers a flexible and open framework for soft-clustering large data sets. In recent years, there has been a growing interest among marketing scholars and practitioners to adopt topic models in various marketing application domains. However, to this date, there is no comprehensive overview of this rapidly evolving field. By analyzing a set of 61 published papers along with conceptual contributions, we systematically review this highly heterogeneous area of research. In doing so, we characterize extant contributions employing topic models in marketing along the dimensions data structures and retrieval of input data, implementation and extensions of basic topic models, and model performance evaluation. Our findings confirm that there is considerable progress done in various marketing sub-areas. However, there is still scope for promising future research, in particular with respect to integrating multiple, dynamic data sources, including time-varying covariates and the combination of exploratory topic models with powerful predictive marketing models.

Globular Clusters contain very old metal-poor stars in different evolutionary stages evolved from the same primordial cloud. Signatures of atomic in stellar interiors are studied in the metal-poor GC M30. Furthermore, traces of cluster internal pollution depleting alpha elements e.g. Mg & O are also found through high precision spectroscopy, which favors the existence of multiple stellar populations within a Globular Cluster. In this work, I use spectroscopic observations of 177 sample stars using the multi object spectrograph GIRAFFE and increasing the initial size of 12 of Scheutwinkel (2018) by 13 new UVES spectrograph sample stars of the Globular Cluster M30 ([Fe/H] = -2.3). The abundances of Fe, Ti, Mg & Ba (GIRAFFE) and Fe, Na, Al & Mg (UVES) are derived through the graphical spectrum analysis program SIU with VI broadband photometric stellar input parameters. The underlying line-formation theory is in LTE and uses 1-dimensional hydrostatic plan-parallel MAFAGS atmospheres with mixing length convection. We confirm an Al-Mg anti-correlation (Spearman ϱs= -0.583) and a correlation (Spearman ϱs= 0.641) between Al-Na in RGB stars as a direct result of being the partner elements of the depleted alpha elements Mg & O caused through NeNa, ON and MgAl cycles. We find similar element ratios [X/Fe] as Carretta et al. (2018) & O‘Malley et al. (2018) favoring the prior existence of multiple stellar populations within M30. Furthermore, we detected a signifcant restoration of abundances in the elements Fe, Mg & Ba towards RGB stars. Fe, Mg and Ti are matching the predictions of the diffusion model T5.8 (Richard et al. 2005) reasonably well. For Ba, we have no current atomic diffusion modeling, so the validation of the results is not possible. The trend of Ti is v-shaped presumably due to stronger radiative accelaration effects for this element. Overall our relative abundance trends are consistent with other Globular Cluster studies by Gruyters et al. (2013&2016), Korn et al. (2007) & Lind (2007).

Moral licensing is a cognitive bias, which enables individuals to behave immorally without threatening their self-image of being a moral person. We investigate this phenomenon in a cross-cultural marketing context. More specifically, this paper addresses the questions (i) how big moral licensing effects typically are and (ii) which factors systematically influence the size of this effect. We approach these questions by conducting a meta-analysis and a meta-regression. Based on a random effects model, the point estimate for the generalized effect size Cohen's d is 0.319 (SE = 0.046; N = 106). Results of a meta-regression advance theory, by showing for the first time that both cultural background and type of comparison explain a substantial amount of the total variation of the effect size of moral licensing. Marketing practitioners wishing to capitalize on moral licensing effects should therefore consider cross-cultural difference, since marketing measures building on this effect may lead to different revenues in different countries.

Personal data is increasingly conceived as a tradable asset. Markets for personal information are emerging and new ways of valuating individuals' data are being proposed. At the same time, legal obligations over protection of personal data and individuals' concerns over its privacy persist. This article outlines some of the economic, technical, social, and ethical issues associated with personal data markets, focusing on the privacy challenges they raise.

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