Bielefeld University

About: Bielefeld University is a education organization based out in Bielefeld, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Population & Quantum chromodynamics. The organization has 10123 authors who have published 26576 publications receiving 728250 citations. The organization is also known as: University of Bielefeld & UNIVERSITAET BIELEFELD.

Phase boundary for the chiral transition in ( 2 + 1 )-flavor QCD at small values of the chemical potential

Abstract: We determine the chiral phase transition line in (2+1)-flavor QCD for small values of the light quark chemical potential. We show that for small values of the chemical potential the curvature of the phase transition line can be deduced from an analysis of scaling properties of the chiral condensate and its susceptibilities. To do so we extend earlier studies of the magnetic equation of state in (2+1)-flavor QCD to finer lattice spacings, aT = 1/8. We use these universal scaling properties of the chiral order parameter to extract the curvature of the transition line at two values of the cut-off, aT = 1/4 and 1/8. We find that cut-off effects are small for the curvature parameter and determine the transition line in the chiral limit to leading order in the light quark chemical potential. We obtain Tc(µq)/Tc(0) = 1 0.059(2)(4)(µq/T) 2 + O(µ 4).

Implementation of self-organizing neural networks for visuo-motor control of an industrial robot

Abstract: The implementation of two neural network algorithms for visuo-motor control of an industrial robot (Puma 562) is reported. The first algorithm uses a vector quantization technique, the 'neural-gas' network, together with an error correction scheme based on a Widrow-Hoff-type learning rule. The second algorithm employs an extended self-organizing feature map algorithm. Based on visual information provided by two cameras, the robot learns to position its end effector without an external teacher. Within only 3000 training steps, the robot-camera system is capable of reducing the positioning error of the robot's end effector to approximately 0.1% of the linear dimension of the work space. By employing adaptive feedback the robot succeeds in compensating not only slow calibration drifts, but also sudden changes in its geometry. Hardware aspects of the robot-camera system are discussed. >

A chimeric transactivator allows tetracycline-responsive gene expression in whole plants

Abstract: Summary The chimeric transcriptional activator tTA, a fusion between the Tn 10 encoded Tet repressor and the activation domain of the Herpes simplex virion protein VP16, was stably expressed in transgenic tobacco plants. It stimulates transcription of the β-glucuronidase (gus) gene from an artificial promoter consisting of 7 tet operators and a TATA-box. Tetracycline, which Interferes with binding of tTA to operator DNA, reduces gus expression over several orders of magnitude. This stringency of regulation suggests that the system can be used to construct transgenic plants encoding a potentially lethal gene product. Furthermore, the specific and fast inactivation of tTA allows study of the stability of RNAs and proteins.

“Too Many betas do not Spoil the Broth”: The Role of Beta Brain Oscillations in Language Processing

Abstract: Over the past 20 years, brain oscillations have proven to be a gateway to the understanding of cognitive processes. It has been shown that different neurocognitive aspects of language processing are associated with brain oscillations at various frequencies. Frequencies in the beta range (13-30 Hz) turned out to be particularly important with respect to cognitive and linguistic manipulations during language processing. Beta activity has been involved in higher-order linguistic functions such as the discrimination of word categories and the retrieval of action semantics as well as semantic memory, and syntactic binding processes, which support meaning construction during sentence processing. From a neurophysiological point of view, the important role of the beta frequencies for such a complex cognitive task as language processing seems reasonable. Experimental evidence suggests that frequencies in the beta range are ideal for maintaining and preserving the activity of neuronal assemblies over time. In particular, recent computational and experimental evidence suggest that beta frequencies are important for linking past and present input and the detection of novelty of stimuli, which are essential processes for language perception as well as production. In addition, the beta frequency’s role in the formation of cell assemblies underlying short-term memory seems indispensable for language analysis. Probably the most important point is the well-known relation of beta oscillations with motor processes. It can be speculated that beta activities reflect the close relationship between language comprehension and motor functions, which is one of the core claims of current theories on embodied cognition. In this article, the importance of beta oscillations for language processing is reviewed based both on findings in psychophysiological and neurophysiological literature.