@book{Laack2022, author = {Laack, Walter van}, title = {Schnittstelle Tod: Was lernen wir durch Corona {\"u}ber Leben und Tod?}, publisher = {van Laack GmbH}, address = {Aachen}, isbn = {978-3-936624-53-3}, pages = {108 Seiten}, year = {2022}, language = {de} } @book{Laack2022, author = {Laack, Walter van}, title = {Aufruf zum Nachdenken: Corona und neue Kriege - Wie kann die Menschheit {\"u}berleben?}, publisher = {van Laack GmbH}, address = {Aachen}, isbn = {978-3-936624-56-4}, pages = {56 Seiten}, year = {2022}, language = {de} } @book{Laack2022, author = {Laack, Walter van}, title = {Greater Than the Entire Universe}, publisher = {van Laack GmbH}, address = {Aachen}, isbn = {978-3-936624-52-6}, pages = {120 Seiten}, year = {2022}, language = {en} } @article{KotliarOrtnerConradietal.2022, author = {Kotliar, Konstantin and Ortner, Marion and Conradi, Anna and Hacker, Patricia and Hauser, Christine and G{\"u}nthner, Roman and Moser, Michaela and Muggenthaler, Claudia and Diehl-Schmid, Janine and Priller, Josef and Schmaderer, Christoph and Grimmer, Timo}, title = {Altered retinal cerebral vessel oscillation frequencies in Alzheimer's disease compatible with impaired amyloid clearance}, series = {Neurobiology of Aging}, volume = {120}, journal = {Neurobiology of Aging}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0197-4580}, doi = {10.1016/j.neurobiolaging.2022.08.012}, pages = {117 -- 127}, year = {2022}, abstract = {Retinal vessels are similar to cerebral vessels in their structure and function. Moderately low oscillation frequencies of around 0.1 Hz have been reported as the driving force for paravascular drainage in gray matter in mice and are known as the frequencies of lymphatic vessels in humans. We aimed to elucidate whether retinal vessel oscillations are altered in Alzheimer's disease (AD) at the stage of dementia or mild cognitive impairment (MCI). Seventeen patients with mild-to-moderate dementia due to AD (ADD); 23 patients with MCI due to AD, and 18 cognitively healthy controls (HC) were examined using Dynamic Retinal Vessel Analyzer. Oscillatory temporal changes of retinal vessel diameters were evaluated using mathematical signal analysis. Especially at moderately low frequencies around 0.1 Hz, arterial oscillations in ADD and MCI significantly prevailed over HC oscillations and correlated with disease severity. The pronounced retinal arterial vasomotion at moderately low frequencies in the ADD and MCI groups would be compatible with the view of a compensatory upregulation of paravascular drainage in AD and strengthen the amyloid clearance hypothesis.}, language = {en} } @article{KleefeldZimmermann2022, author = {Kleefeld, Andreas and Zimmermann, M.}, title = {Computing Elastic Interior Transmission Eigenvalues}, series = {Integral Methods in Science and Engineering}, journal = {Integral Methods in Science and Engineering}, editor = {Constanda, Christian and Bodmann, Bardo E.J. and Harris, Paul J.}, publisher = {Birkh{\"a}user}, address = {Cham}, isbn = {978-3-031-07171-3}, doi = {10.1007/978-3-031-07171-3_10}, pages = {139 -- 155}, year = {2022}, abstract = {An alternative method is presented to numerically compute interior elastic transmission eigenvalues for various domains in two dimensions. This is achieved by discretizing the resulting system of boundary integral equations in combination with a nonlinear eigenvalue solver. Numerical results are given to show that this new approach can provide better results than the finite element method when dealing with general domains.}, language = {en} } @article{KaulenSchwabedalSchneideretal.2022, author = {Kaulen, Lars and Schwabedal, Justus T. C. and Schneider, Jules and Ritter, Philipp and Bialonski, Stephan}, title = {Advanced sleep spindle identification with neural networks}, series = {Scientific Reports}, volume = {12}, journal = {Scientific Reports}, number = {Article number: 7686}, publisher = {Springer Nature}, address = {London}, issn = {2045-2322}, doi = {10.1038/s41598-022-11210-y}, pages = {1 -- 10}, year = {2022}, abstract = {Sleep spindles are neurophysiological phenomena that appear to be linked to memory formation and other functions of the central nervous system, and that can be observed in electroencephalographic recordings (EEG) during sleep. Manually identified spindle annotations in EEG recordings suffer from substantial intra- and inter-rater variability, even if raters have been highly trained, which reduces the reliability of spindle measures as a research and diagnostic tool. The Massive Online Data Annotation (MODA) project has recently addressed this problem by forming a consensus from multiple such rating experts, thus providing a corpus of spindle annotations of enhanced quality. Based on this dataset, we present a U-Net-type deep neural network model to automatically detect sleep spindles. Our model's performance exceeds that of the state-of-the-art detector and of most experts in the MODA dataset. We observed improved detection accuracy in subjects of all ages, including older individuals whose spindles are particularly challenging to detect reliably. Our results underline the potential of automated methods to do repetitive cumbersome tasks with super-human performance.}, language = {en} } @article{HerssensCowburnAlbrachtetal.2022, author = {Herssens, Nolan and Cowburn, James and Albracht, Kirsten and Braunstein, Bjoern and Cazzola, Dario and Colyer, Steffi and Minetti, Alberto E. and Pavei, Gaspare and Rittweger, J{\"o}rn and Weber, Tobias and Green, David A.}, title = {Movement in low gravity environments (MoLo) programme - the MoLo-L.O.O.P. study protocol}, series = {PLOS ONE / Public Library of Science}, volume = {17}, journal = {PLOS ONE / Public Library of Science}, number = {11}, editor = {Cattaneo, Luigi}, publisher = {Plos}, address = {San Francisco}, issn = {1932-6203}, doi = {10.1371/journal.pone.0278051}, pages = {e0278051}, year = {2022}, abstract = {Exposure to prolonged periods in microgravity is associated with deconditioning of the musculoskeletal system due to chronic changes in mechanical stimulation. Given astronauts will operate on the Lunar surface for extended periods of time, it is critical to quantify both external (e.g., ground reaction forces) and internal (e.g., joint reaction forces) loads of relevant movements performed during Lunar missions. Such knowledge is key to predict musculoskeletal deconditioning and determine appropriate exercise countermeasures associated with extended exposure to hypogravity.}, language = {en} } @article{HarrisKleefeld2022, author = {Harris, Isaac and Kleefeld, Andreas}, title = {Analysis and computation of the transmission eigenvalues with a conductive boundary condition}, series = {Applicable Analysis}, volume = {101}, journal = {Applicable Analysis}, number = {6}, publisher = {Taylor \& Francis}, address = {London}, issn = {1563-504X}, doi = {10.1080/00036811.2020.1789598}, pages = {1880 -- 1895}, year = {2022}, abstract = {We provide a new analytical and computational study of the transmission eigenvalues with a conductive boundary condition. These eigenvalues are derived from the scalar inverse scattering problem for an inhomogeneous material with a conductive boundary condition. The goal is to study how these eigenvalues depend on the material parameters in order to estimate the refractive index. The analytical questions we study are: deriving Faber-Krahn type lower bounds, the discreteness and limiting behavior of the transmission eigenvalues as the conductivity tends to infinity for a sign changing contrast. We also provide a numerical study of a new boundary integral equation for computing the eigenvalues. Lastly, using the limiting behavior we will numerically estimate the refractive index from the eigenvalues provided the conductivity is sufficiently large but unknown.}, language = {en} } @article{GaigallGerstenbergTrinh2022, author = {Gaigall, Daniel and Gerstenberg, Julian and Trinh, Thi Thu Ha}, title = {Empirical process of concomitants for partly categorial data and applications in statistics}, series = {Bernoulli}, volume = {28}, journal = {Bernoulli}, number = {2}, publisher = {International Statistical Institute}, address = {Den Haag, NL}, issn = {1573-9759}, doi = {10.3150/21-BEJ1367}, pages = {803 -- 829}, year = {2022}, abstract = {On the basis of independent and identically distributed bivariate random vectors, where the components are categorial and continuous variables, respectively, the related concomitants, also called induced order statistic, are considered. The main theoretical result is a functional central limit theorem for the empirical process of the concomitants in a triangular array setting. A natural application is hypothesis testing. An independence test and a two-sample test are investigated in detail. The fairly general setting enables limit results under local alternatives and bootstrap samples. For the comparison with existing tests from the literature simulation studies are conducted. The empirical results obtained confirm the theoretical findings.}, language = {en} } @inproceedings{Gaigall2022, author = {Gaigall, Daniel}, title = {On Consistent Hypothesis Testing In General Hilbert Spaces}, series = {Proceedings of the 4th International Conference on Statistics: Theory and Applications (ICSTA'22)}, booktitle = {Proceedings of the 4th International Conference on Statistics: Theory and Applications (ICSTA'22)}, publisher = {Avestia Publishing}, address = {Orl{\´e}ans, Kanada}, doi = {10.11159/icsta22.157}, pages = {Paper No. 157}, year = {2022}, abstract = {Inference on the basis of high-dimensional and functional data are two topics which are discussed frequently in the current statistical literature. A possibility to include both topics in a single approach is working on a very general space for the underlying observations, such as a separable Hilbert space. We propose a general method for consistently hypothesis testing on the basis of random variables with values in separable Hilbert spaces. We avoid concerns with the curse of dimensionality due to a projection idea. We apply well-known test statistics from nonparametric inference to the projected data and integrate over all projections from a specific set and with respect to suitable probability measures. In contrast to classical methods, which are applicable for real-valued random variables or random vectors of dimensions lower than the sample size, the tests can be applied to random vectors of dimensions larger than the sample size or even to functional and high-dimensional data. In general, resampling procedures such as bootstrap or permutation are suitable to determine critical values. The idea can be extended to the case of incomplete observations. Moreover, we develop an efficient algorithm for implementing the method. Examples are given for testing goodness-of-fit in a one-sample situation in [1] or for testing marginal homogeneity on the basis of a paired sample in [2]. Here, the test statistics in use can be seen as generalizations of the well-known Cram{\´e}rvon-Mises test statistics in the one-sample and two-samples case. The treatment of other testing problems is possible as well. By using the theory of U-statistics, for instance, asymptotic null distributions of the test statistics are obtained as the sample size tends to infinity. Standard continuity assumptions ensure the asymptotic exactness of the tests under the null hypothesis and that the tests detect any alternative in the limit. Simulation studies demonstrate size and power of the tests in the finite sample case, confirm the theoretical findings, and are used for the comparison with concurring procedures. A possible application of the general approach is inference for stock market returns, also in high data frequencies. In the field of empirical finance, statistical inference of stock market prices usually takes place on the basis of related log-returns as data. In the classical models for stock prices, i.e., the exponential L{\´e}vy model, Black-Scholes model, and Merton model, properties such as independence and stationarity of the increments ensure an independent and identically structure of the data. Specific trends during certain periods of the stock price processes can cause complications in this regard. In fact, our approach can compensate those effects by the treatment of the log-returns as random vectors or even as functional data.}, language = {en} }