Tilburg University

About: Tilburg University is a education organization based out in Tilburg, Noord-Brabant, Netherlands. It is known for research contribution in the topics: Population & Context (language use). The organization has 5550 authors who have published 22330 publications receiving 791335 citations.

What Goals Do Business Leaders Pursue? A Study in Fifteen Countries

Abstract: Goals-in-use of successful businesspersons were rated by over 1,800 junior managers and professionals, attending evening MBA courses at local universities in 15 countries. A hierarchical cluster analysis of perceived goals divided the countries into seven clusters. The relative ordering of goals within these clusters suggested seven different archetypal business leader roles. Perceptions correlated significantly with national wealth, as well as with dimensions of national culture.

Usefulness of type D personality in predicting five-year cardiac events above and beyond concurrent symptoms of stress in patients with coronary heart disease.

Abstract: Psychological stress and type D personality have been associated with adverse cardiac prognosis, but little is known about their relative effect on the pathogenesis of coronary heart disease (CHD). "Type D" refers to the tendency to experience negative emotions and to inhibit the expression of these emotions in social interactions. We investigated the relative effect of stress and type D personality on prognosis at 5-year follow-up. At baseline, 337 patients with CHD who participated in cardiac rehabilitation filled in the General Health Questionnaire (psychological stress) and the Type D personality scale. Patients were followed for 5 years. The end point was major adverse cardiac events, which were defined as a composite of cardiac death, myocardial infarction, and cardiac revascularization (coronary artery bypass grafting/percutaneous coronary intervention). There were 46 major adverse cardiac events at follow-up, including 4 deaths and 8 myocardial infarctions. Type D patients had an increased risk of death/infarction (odds ratio 4.84, 95% confidence interval 1.42 to 16.52, p = 0.01) compared with non-type D patients, independent of disease severity. Stress (p = 0.011) and type D (p = 0.001) were related to an increased risk of developing a major adverse cardiac event after adjusting for gender, age, and biomedical risk factors. Multivariate analysis yielded left ventricular ejection fraction < or =40%, no treatment with coronary artery bypass grafting, and type D personality (odds ratio 2.90, 95% confidence interval 1.42 to 5.92, p = 0.003) as independent predictors of major adverse cardiac events, whereas psychological stress was marginally significant (odds ratio 2.01, 95% confidence interval 0.99 to 4.11, p = 0.054). In conclusion, type D personality is a psychological factor that may optimize risk stratification in patients with CHD. Type D reflects more than temporary changes in general stress level because it predicted cardiac events after controlling for concurrent symptoms of stress.

Graph-based generation of referring expressions

Abstract: This article describes a new approach to the generation of referring expressions. We propose to formalize a scene (consisting of a set of objects with various properties and relations) as a labeled directed graph and describe content selection (which properties to include in a referring expression) as a subgraph construction problem. Cost functions are used to guide the search process and to give preference to some solutions over others. The current approach has four main advantages: (1) Graph structures have been studied extensively, and by moving to a graph perspective we get direct access to the many theories and algorithms for dealing with graphs; (2) many existing generation algorithms can be reformulated in terms of graphs, and this enhances comparison and integration of the various approaches; (3) the graph perspective allows us to solve a number of problems that have plagued earlier algorithms for the generation of referring expressions; and (4) the combined use of graphs and cost functions paves the way for an integration of rule-based generation techniques with more recent stochastic approaches.