Algebraic Tail Decay of Condition Numbers for Random Conic Systems under a General Family of Input Distributions

We consider the conic feasibility problem associated with linear homogeneous systems of inequalities. The complexity of iterative algorithms for solving this problem depends on a condition number. When studying the typical behaviour of algorithms under stochastic input one is therefore naturally led to investigate the fatness of the distribution tails of the random condition number that ensues. We study an unprecedently general class of probability models for the random input matrix and show that the tails decay at algebraic rates with an exponent that naturally emerges when applying a theory of uniform absolute continuity which is also developed in this paper.\ud \ud Raphael Hauser was supported through grant NAL/00720/G from the Nuffield Foundation and through grant GR/M30975 from the Engineering and Physical Sciences Research Council of the UK. Tobias Müller was partially supported by EPSRC, the Department of Statistics, Bekker-la-Bastide fonds, Dr Hendrik Muller's Vaderlandsch fonds, and Prins Bernhard Cultuurfonds

Application of adiabatic pulses for magnetic Resonance Sounding – Pulse shapes and resolution

Magnetic Resonance Sounding (MRS) can image the spatial distribution of hydrologically relevant parameters in in the subsurface. However, the application of MRS is often limited by its low signal-to-noise ratio. The use of adiabatic excitation pulses show promising features to overcome this limitation. In this work, we study practical considerations when applying adiabatic pulses for MRS, i.e. calculation of the sensitivity kernel for varying pulse shapes and vertical resolution. The pulse shape is crucial for the performance of adiabatic pulses. We investigate the shapes of adiabatic pulses recorded during a MRS and observe small systematic deviations from the theoretical predicted pulse shape and variations between different pulse strengths. We show that the overall impact on the obtained sounding curve and inversion result was small. This enables to limit the time consuming modelling of the spin dynamic to one representative pulse shape, which significantly speeds up the calculation of the sensitivity kernel, necessary for the interpretation of MRS. Additionally, we show that on-resonance excitation generally outperforms adiabatic excitation concerning vertical resolution and depth of investigation (both up to a factor of two). This is true for a wide range of noise conditions. For a very shallow depth interval compared to the loop size, however, adiabatic excitation features improved imaging capabilities. © 2020 The Author

Ex-Ante Prediction of Disruptive Innovation: The Case of Battery Technologies

Battery technologies represent a highly relevant field that is undergoing conversions in the context of, for instance, battery electric vehicles or stationary power storage for renewable energies. Currently, lithium-ion batteries represent the predominant technology that has, however, a considerable environmental impact that could hinder the emergence of sustainable energy systems. Driven by these conversions, several authors claim that potentially disruptive technologies could occur. The concept of disruptive innovation has been highly regarded in research and practice, but has only been successfully regarded from an ex-post perspective. However, without the possibility to establish ex-ante predictions of disruptive innovation, several authors disregard the concept of having significant relevance for practice. In response to this research gap, the present paper attempts to establish an ex-ante prediction of potential disruptive innovation. The method is based on the disruption hazard model by Sood and Tellis, testing seven hypotheses regarding a potential disruption hazard of redox-flow batteries towards lithium-ion batteries. The paper finds that redox-flow batteries could represent a disruptive technology, but this evaluation is limited to an expert evaluation. The authors discuss this finding, as the technical characteristics of redox-flow batteries support its role as a potential disruptive innovation, concluding with implications, limitations as well as suggestions for future research

The role of material engineering within the concept of an integrated water resources management

By means of a case study, the successful implementation of a rheologically optimised cement-based mortar for the construction as well as for the rehabiliation of rain water cisterns is presented in this paper..

Convolutional Neural Networks for Epileptic Seizure Prediction

Epilepsy is the most common neurological disorder and an accurate forecast of seizures would help to overcome the patient's uncertainty and helplessness. In this contribution, we present and discuss a novel methodology for the classification of intracranial electroencephalography (iEEG) for seizure prediction. Contrary to previous approaches, we categorically refrain from an extraction of hand-crafted features and use a convolutional neural network (CNN) topology instead for both the determination of suitable signal characteristics and the binary classification of preictal and interictal segments. Three different models have been evaluated on public datasets with long-term recordings from four dogs and three patients. Overall, our findings demonstrate the general applicability. In this work we discuss the strengths and limitations of our methodology.Comment: accepted for MLESP 201

A red/far-red light-responsive bi-stable toggle switch to control gene expression in mammalian cells

Growth and differentiation of multicellular systems is orchestrated by spatially restricted gene expression programs in specialized subpopulations. The targeted manipulation of such processes by synthetic tools with high-spatiotemporal resolution could, therefore, enable a deepened understanding of developmental processes and open new opportunities in tissue engineering. Here, we describe the first red/far-red light-triggered gene switch for mammalian cells for achieving gene expression control in time and space. We show that the system can reversibly be toggled between stable on- and off-states using short light pulses at 660 or 740 nm. Red light-induced gene expression was shown to correlate with the applied photon number and was compatible with different mammalian cell lines, including human primary cells. The light-induced expression kinetics were quantitatively analyzed by a mathematical model. We apply the system for the spatially controlled engineering of angiogenesis in chicken embryos. The system's performance combined with cell- and tissue-compatible regulating red light will enable unprecedented spatiotemporally controlled molecular interventions in mammalian cells, tissues and organisms