University of Jena

About: University of Jena is a education organization based out in Jena, Thüringen, Germany. It is known for research contribution in the topics: Laser & Population. The organization has 22198 authors who have published 45159 publications receiving 1401514 citations. The organization is also known as: Friedrich-Schiller-Universität Jena & Friedrich Schiller University Jena.

Latent state–trait theory and research in personality and individual differences

Abstract: Latent state–trait (LST) theory is a generalization of classical test theory designed to take account of the fact that psychological measurement does not take place in a situational vacuum. The basic concepts of latent state–trait theory (LST theory) are introduced. The core of LST theory consists of two decompositions: (a) the decomposition of any observed score into latent state and measurement error, and (b) the decomposition of any latent state into latent trait and latent state residual representing situational and/or interaction effects. Latent states and latent traits are defined as special conditional expectations. A score on a latent state variable is defined as the expectation of an observable variable Yik given a person in a situation whereas a score on a latent trait variable is the expectation of Yik given a person. The theory also comprises the definition of consistency, occasion specificity, reliability, and stability coefficients. An overview of different models of LST theory is given. It is shown how different research questions of personality psychology can be and have been analysed within the LST framework and why research in personality and individual differences can profit from LST theory and methodology. Copyright © 1999 John Wiley & Sons, Ltd.

Bayesian localization microscopy reveals nanoscale podosome dynamics

Abstract: We describe a localization microscopy analysis method that is able to extract results in live cells using standard fluorescent proteins and xenon arc lamp illumination. Our Bayesian analysis of the blinking and bleaching (3B analysis) method models the entire dataset simultaneously as being generated by a number of fluorophores that may or may not be emitting light at any given time. The resulting technique allows many overlapping fluorophores in each frame and unifies the analysis of the localization from blinking and bleaching events. By modeling the entire dataset, we were able to use each reappearance of a fluorophore to improve the localization accuracy. The high performance of this technique allowed us to reveal the nanoscale dynamics of podosome formation and dissociation throughout an entire cell with a resolution of 50 nm on a 4-s timescale.