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We prove new structural results for the rational homotopy type of the classifying space B aut(X) of fibrations with fiber a simply connected finite CW-complex X.We first study nilpotent covers of B aut(X) and show that their rational cohomology groups are algebraic representations of the associated transformation groups. For the universal cover, this yields an extension of the Sullivan-Wilkerson theorem to higher homotopy and cohomology groups. For the cover corresponding to the kernel of the homology representation, this proves algebraicity of the cohomology of the homotopy Torelli space.For the cover that classifies what we call normal unipotent fibrations, we then prove the stronger result that there exists a nilpotent dg Lie algebra g(X) in algebraic representations that models its equivariant rational homotopy type. This leads to an algebraic model for the space B aut(X) and to a description of its rational cohomology ring as the cohomology of a certain arithmetic group Γ(X) with coefficients in the Chevalley-Eilenberg cohomology of g(X). This has strong structural consequences for the cohomology ring and, in certain cases, allows it to be completely determined using invariant theory and calculations with modular forms. We illustrate these points with concrete examples.As another application, we significantly improve on certain results on selfhomotopy equivalences of highly connected even-dimensional manifolds due to Berglund-Madsen, and we prove parallel new results in odd dimensions.

Methods based on the quantification of the total amount of DNA in samples are unsuitable for ancient samples as they overestimate the amount of DNA presumably due to the presence of microbial DNA. Real-time qPCR methods give undervalued results due to DNA damage and the presence of PCR inhibitors. DNA quantification methods based on fragment analysis show not only the quantity of DNA but also fragment length.

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This paper describes methods for theoretical modeling of inter-arrival time of impulse noise and presents a new model based on the application of general mathematical distributions, together with its implementation in MATLAB. It also discusses the suitability of this model for development and testing of digital communication systems intended for deployment on high-voltage power distribution lines.

Since its approval as an adjunct treatment for refractory partial epilepsy, the positive effects of vagus nerve stimulation (VNS) on seizure frequency and severity have been supported by many studies. Seizure reduction of more than 50 % can be expected in at least 50 % of patients. However, a complete post-VNS seizure freedom is rarely achieved and 25 % of patients do not benefi t from VNS. Our study provides an overview of the potential predictors of VNS response, from the most simple and basic data to sophisticated EEG processing studies and functional imaging studying brain connectivity. The data support better outcomes in younger patients with early VNS implantation, in patients with posttraumatic epilepsy or tuberous sclerosis, and in patients without bilateral interictal epileptiform discharges. The variability of heart activity has also been studied with some promising results. Because the generally accepted hypothesis of the VNS mechanism is the modulation of synaptic activity in multiple cortical and subcortical regions of the brain, the studies of brain response to external stimulation and/or of brain connectivity were used for models predicting the effect of VNS in individual patients. Although the predictive value of these models is high, the required special equipment and sophisticated mathematical tools limit their routine use (Ref. 58).

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