University of Mannheim

About: University of Mannheim is a education organization based out in Mannheim, Germany. It is known for research contribution in the topics: Context (language use) & Politics. The organization has 4448 authors who have published 12918 publications receiving 446557 citations. The organization is also known as: Uni Mannheim & UMA.

Carnosine prevents apoptosis of glomerular cells and podocyte loss in STZ diabetic rats.

Abstract: Background/Aims: We identified carnosinase-1 (CN-1) as risk-factor for diabetic nephropathy (DN). Carnosine, the substrate for CN-1, supposedly is a protective factor regarding diabetic complications. In this study, we hypothesized that carnosine administration to diabetic rats might protect the kidneys from glomerular apoptosis and podocyte loss. Methods: We examined the effect of oral L-carnosine administration (1g/kg BW per day) on apoptosis, podocyte loss, oxidative stress, AGEs and hexosamine pathway in kidneys of streptozotocin-induced diabetic Wistar rats after 3 months of diabetes and treatment. Results: Hyperglycemia significantly reduced endogenous kidney carnosine levels. In parallel, podocyte numbers significantly decreased (-21% compared to non-diabetics, p

Dissociation in victims of childhood abuse or neglect: a meta-analytic review.

Abstract: Childhood abuse and neglect are associated with dissociative symptoms in adulthood. However, empirical studies show heterogeneous results depending on the type of childhood abuse or neglect and other maltreatment characteristics. In this meta-analysis, we systematically investigated the relationship between childhood interpersonal maltreatment and dissociation in 65 studies with 7352 abused or neglected individuals using the Dissociative Experience Scale (DES). We extracted DES-scores for abused and non-abused populations as well as information about type of abuse/neglect, age of onset, duration of abuse, and relationship to the perpetrator. Random-effects models were used for data synthesis, and meta-regression was used to predict DES-scores in abused populations from maltreatment characteristics. The results revealed higher dissociation in victims of childhood abuse and neglect compared with non-abused or neglected subsamples sharing relevant population features (MAbuse = 23.5, MNeglect = 18.8, MControl = 13.8) with highest scores for sexual and physical abuse. An earlier age of onset, a longer duration of abuse, and parental abuse significantly predicted higher dissociation scores. This meta-analysis underlines the importance of childhood abuse/neglect in the etiology of dissociation. The identified moderators may inform risk assessment and early intervention to prevent the development of dissociative symptoms.

Retaliatory Behavior to New Product Entry

Abstract: In this article, the authors focus on the defense strategies that firms pursue when threatened by rival new products in their markets. They investigate retaliation as a multidimensional construct. ...

Weakly supervised learning for fake news detection on Twitter

Abstract: The problem of automatic detection of fake news in social media, e.g., on Twitter, has recently drawn some attention. Although, from a technical perspective, it can be regarded as a straight-forward, binary classification problem, the major challenge is the collection of large enough training corpora, since manual annotation of tweets as fake or non-fake news is an expensive and tedious endeavor. In this paper, we discuss a weakly supervised approach, which automatically collects a large-scale, but very noisy training dataset comprising hundreds of thousands of tweets. During collection, we automatically label tweets by their source, i.e., trustworthy or untrustworthy source, and train a classifier on this dataset. We then use that classifier for a different classification target, i.e., the classification of fake and non-fake tweets. Although the labels are not accurate according to the new classification target (not all tweets by an untrustworthy source need to be fake news, and vice versa), we show that despite this unclean inaccurate dataset, it is possible to detect fake news with an F1 score of up to 0.9.

September 11 and Stock Return Expectations of Individual Investors

Abstract: This study offers the unique opportunity to analyze how an unprecedented crisis such as the September 11 tragedy in uences expected returns and volatility forecasts of individual investors. Via e-mail, we asked a randomly selected group of individual investors with accounts at a German online broker to answer an internet questionnaire at the beginning of August, 2001. A second e-mail to the investors who have not yet answered, scheduled five weeks later, was postponed due to the terror attacks until September 20, which was exactly the day with the lowest share prices in Germany in the year 2001. Based on the answers to questions concerning stock market predictions, we find that return forecasts of the investors in our sample are significantly higher after September 11. The actual returns from the respective time of response until the end of the year 2001 are overestimated in both groups. The second group of investors states return forecasts that are approximately twice as high as the true realized returns. After the terror attacks, volatility forecasts are higher than before September 11. In two out of four cases, historical volatilities are overestimated. Therefore, investors are not generally overconfident in the way that they underestimate the variance of stock returns. Differences of opinion with regard to return forecasts are lower after the terror attacks whereas differences of opinion concerning volatility forecasts are mainly unaffected. Furthermore, differences of opinion are generally higher with regard to return (point) forecasts when compared to differences of opinion with regard volatility forecasts.