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A commentary on Commentary: Aesthetic Pleasure versus Aesthetic Interest: The Two Routes to Aesthetic Liking by Consoli, G. (2017). Front. Psychol. 8:1197. doi: 10.3389/fpsyg.2017.01197
In his commentary on the paper “Aesthetic Pleasure versus Aesthetic Interest: The Two Routes to Aesthetic Liking,” authored by Jan R. Landwehr and myself (Graf and Landwehr, 2017), Consoli (2017) deplores two aspects of our paper. First, an inadequate definition and operationalization of the key constructs aesthetic pleasure, aesthetic interest, and aesthetic liking, respectively aesthetic attractiveness. Second, the conclusions drawn from our empirical studies. While I acknowledge that one may have a different theoretical perspective on aesthetic perception and evaluation, it appears that Consoli's (2017) commentary does not even address the empirical data of our studies but only our theoretical assumptions and definitions. In the following, I will address Consoli's (2016, 2017) arguments in more detail, and I will corroborate our theoretical reasoning with the empirical data of our studies (Graf and Landwehr, 2017).....
Inhibitory interneurons govern virtually all computations in neocortical circuits and are in turn controlled by neuromodulation. While a detailed understanding of the distinct marker expression, physiology, and neuromodulator responses of different interneuron types exists for rodents and recent studies have highlighted the role of specific interneurons in converting rapid neuromodulatory signals into altered sensory processing during locomotion, attention, and associative learning, it remains little understood whether similar mechanisms exist in human neocortex. Here, we use whole-cell recordings combined with agonist application, transgenic mouse lines, in situ hybridization, and unbiased clustering to directly determine these features in human layer 1 interneurons (L1-INs). Our results indicate pronounced nicotinic recruitment of all L1-INs, whereas only a small subset co-expresses the ionotropic HTR3 receptor. In addition to human specializations, we observe two comparable physiologically and genetically distinct L1-IN types in both species, together indicating conserved rapid neuromodulation of human neocortical circuits through layer 1.
Privacy concerns as well as trust and risk beliefs are important factors that can influence users’ decision to use a service. One popular model that integrates these factors is relating the Internet Users Information Privacy Concerns (IUIPC) construct to trust and risk beliefs. However, studies haven’t yet applied it to a privacy enhancing technology (PET) such as an anonymization service. Therefore, we conducted a survey among 416 users of the anonymization service JonDonym [1] and collected 141 complete questionnaires. We rely on the IUIPC construct and the related trust-risk model and show that it needs to be adapted for the case of PETs. In addition, we extend the original causal model by including trust beliefs in the anonymization service provider and show that they have a significant effect on the actual use behavior of the PET.
Considering the circumstance that literature dealing with the economic performance of agri-food businesses in general, or particularly with the German agricultural sector, mainly deals with strictly agricultural-related theory in order to explain the economic success of agri-food businesses, the present paper aims to extend existing discourses to further areas of thought. Consequently, the characteristics: a) increased size of agribusiness, b) pull-strategies, c) the development of new markets and d) focus on the processing industry, that all correspond to the current picture of the German agricultural sector and are considered to be significantly responsible for recently managing to outpace the French agri-food sector, will be first explained in their success against the background of mainly non-agricultural-related literature. By doing so helpful and rather unnoted perspectives can be contributed to existing discourses. Second, the paper presents scatter plots which portray correlations between a) the added value of agriculture and the regular labor force, b) the added value of agriculture and the number of agricultural holdings and c) the added value of agriculture and the number of enterprises concerning milk consumption. Corresponding scatter plots which show different developments in Germany and France can be related to the findings of the first part of the paper and allow new perspectives in existing discourses as well.
Advanced machine learning has achieved extraordinary success in recent years. “Active” operational risk beyond ex post analysis of measured-data machine learning could provide help beyond the regime of traditional statistical analysis when it comes to the “known unknown” or even the “unknown unknown.” While machine learning has been tested successfully in the regime of the “known,” heuristics typically provide better results for an active operational risk management (in the sense of forecasting). However, precursors in existing data can open a chance for machine learning to provide early warnings even for the regime of the “unknown unknown.”