University of Duisburg-Essen

About: University of Duisburg-Essen is a education organization based out in Essen, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 16072 authors who have published 39972 publications receiving 1109199 citations.

The influence of proteins on the dispersability and cell-biological activity of silver nanoparticles

Abstract: Spherical silver nanoparticles with a diameter of 50 ± 20 nm and stabilized with either poly(N-vinylpyrrolidone) (PVP) or citrate were dispersed in different cell culture media: (i) pure RPMI, (ii) RPMI containing up to 10% of bovine serum albumin (BSA), and (iii) RPMI containing up to 10% of fetal calf serum (FCS). The agglomeration behavior of the nanoparticles was studied with dynamic light scattering and optical microscopy of individually tracked single particles. Whereas strong agglomeration was observed in pure RPMI and in the RPMI–BSA mixture within a few hours, the particles remained well dispersed in RPMI–FCS. In addition, the biological effect of PVP-stabilized silver nanoparticles and of silver ions on human mesenchymal stem cells (hMSCs) was studied in pure RPMI and also in RPMI–BSA and RPMI–FCS mixtures, respectively. Both proteins considerably increased the cell viability in the presence of silver ions and as well as silver nanoparticles, indicating a binding of silver by these proteins.

Internet addiction: coping styles, expectancies, and treatment implications.

Abstract: Internet addiction has become a serious mental health condition in many countries. To better understand the clinical implications of Internet addiction, this study tested statistically a new theoretical model illustrating underlying cognitive mechanisms contributing to development and maintenance of the disorder. The model differentiates between a generalized Internet addiction (GIA) and specific forms. This study tested the model on GIA on a population of general Internet users. The findings from 1019 users showed that the hypothesized structural equation model explained 63.5% of the variance of GIA symptoms, as measured by the short version of the Internet Addiction Test (s-IAT). Using psychological and personality testing, the results show that a person’s specific cognitions (poor coping and cognitive expectations) increased the risk for generalized Internet addiction. These two factors mediated the symptoms of GIA if other risk factors were present such as depression, social anxiety, low self-esteem, low self-efficacy, and high stress vulnerability to name a few areas that were measured in the study. The model shows that individuals with high coping skills and no expectancies that the Internet can be used to increase positive or reduce negative mood are less likely to engage in problematic Internet use, even when other personality or psychological vulnerabilities are present. The implications for treatment include a clear cognitive component to the development of generalized Internet addiction and the need to assess a patient’s coping style and cognitions and improve faulty thinking to reduce symptoms and engage in recovery.

An Experimental Study on Emotional Reactions Towards a Robot

Abstract: Although robots are starting to enter into our professional and private lives, little is known about the emotional effects which robots elicit. However, insights into this topic are an important prerequisite when discussing, for example, ethical issues regarding the question of what role we (want to) allow robots to play in our lives. In line with the Media Equation, humans may react towards robots as they do towards humans, making it all the more important to carefully investigate the preconditions and consequences of contact with robots. Based on assumptions on the socialness of reactions towards robots and anecdotal evidence of emotional attachments to robots (e.g. Klamer and BenAllouch in Trappl R. (ed.), Proceedings of EMCSR 2010, Vienna, 2010; Klamer and BenAllouch in Proceedings of the 27th International Conference on Human Factors in Computing Systems (CHI-2010), Atlanta, GA. ACM, New York, 2010; Kramer et al. in Appl. Artif. Intell. 25(6):474–502, 2011), we conducted a study that provides further insights into the question of whether humans show emotional reactions towards Ugobe’s Pleo, which is shown in different situations. We used a 2×2 design with one between-subjects factor “prior interaction with the robot” (never seen the robot before vs. 10-minute interaction with the robot) and a within-subject factor “type of video” (friendly interaction video vs. torture video). Following a multi-method approach, we assessed participants’ physiological arousal and self-reported emotions as well as their general evaluation of the videos and the robot. In line with our hypotheses, participants showed increased physiological arousal during the reception of the torture video as compared to the normal video. They also reported fewer positive and more negative feelings after the torture video and expressed empathic concern for the robot. It appears that the acquaintance with the robot does not play a role, as “prior interaction with the robot” showed no effect.

Unsupervised texture segmentation of images using tuned matched Gabor filters

Abstract: Recent studies have confirmed that the multichannel Gabor decomposition represents an excellent tool for image segmentation and boundary detection. Unfortunately, this approach when used for unsupervised image analysis tasks imposes excessive storage requirements due to the nonorthogonality of the basis functions and is computationally highly demanding. In this correspondence, we propose a novel method for efficient image analysis that uses tuned matched Gabor filters. The algorithmic determination of the parameters of the Gabor filters is based on the analysis of spectral feature contrasts obtained from iterative computation of pyramidal Gabor transforms with progressive dyadic decrease of elementary cell sizes. The method requires no a priori knowledge of the analyzed image so that the analysis is unsupervised. Computer simulations applied to different classes of textures illustrate the matching property of the tuned Gabor filters derived using our determination algorithm. Also, their capability to extract significant image information and thus enable an easy and efficient low-level image analysis will be demonstrated. >