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Netzwerk Nagetier-übertragene Pathogene: Monitoring von Hantavirus-Infektionen in Deutschland
(2009)
An efficient and robust electrical resistivity tomographic inversion algorithm based on the Levenberg-Marquardt method is considered to obtain quantities like grain size, source discrimination and particle size distribution. The corresponding model in two-dimensions is based on the Maxwell equations and leads to a partial differential equation with mixed Dirichlet-Neumann boundary conditions. The forward problem is solved numerically with the finite-difference method. However, the inverse problem at hand is a classic nonlinear and ill-posed parameter estimation problem. Linearizing it and applying the Tikhonov regularization method yields an iterative scheme, the Levenberg-Marquardt method. Several systems of equations of large size have to be solved efficiently in each iteration step which is accomplished by the conjugate gradient method without setting up the corresponding matrix. Instead fast matrix-vector multiplications are performed directly. Therefore, the derivative and its adjoint for the parameter-to-solution map are needed. Numerical results demonstrate the performance of our method as well as the possibility to reconstruct some of the desired parameters.
Microstructure development and hardness of a powder metallurgical multi phase gamma-TiAl based alloy
(2012)
Heterogeneously-Catalyzed Hydrogenation of Carbon Dioxide to Methane using RuNi Bimetallic Catalysts
(2015)
Quantile filters, or rank-order filters, are local image filters which assign quantiles of intensities of the input image within neighbourhoods as output image values. Combining a multivariate quantile definition developed in matrix-valued morphology with a recently introduced mapping between the RGB colour space and the space of symmetric 2×2 matrices, we state a class of colour image quantile filters, along with a class of morphological gradient filters derived from these. Using amoeba structuring elements, we devise image-adaptive versions of both filter classes. Experiments demonstrate the favourable properties of the filters.
Waste electrical and electronic equipment is a complex waste stream and treatment options that work for one waste category or product may not be appropriate for others. A comprehensive case study has been performed for plastic-rich fractions that are treated in German dismantling centres. Plastics from TVs, monitors and printers and small household appliances have been characterised extensively. Based on the characterisation results, state-of-the-art treatment technologies have been combined to design an optimised recycling and upgrade process for each input fraction. High-impact polystyrene from TV casings that complies with the European directive on the restriction of hazardous substances (RoHS) was produced by applying continuous density separation with yields of about 60%. Valuable acrylonitrile butadiene styrene/ polycarbonate can be extracted from monitor and printer casings by near-
infrared-based sorting. Polyolefins and/or a halogen-free fraction of mixed styrenics can be sorted out by density separation from monitors and printers and small household appliances. Emerging separation technologies are discussed to improve recycling results.
Chemosensitive properties of 4,4′-dimethoxy-2,2′-bipyrrole and 4,4′-dibuthoxy-2,2′-bipyrrole were investigated. These new conductive polymers were polymerized by cyclic voltammetry on the platinum and gold interdigitated electrodes designed for 2- and 4-point measurement of lateral conductivity. Thus, obtained polymers demonstrated high sensitivity to HCl in the parts per million concentration range. Kinetics of the gaseous HCl influence on the ratios of conductivities measured by 2- and 4-point techniques was analyzed. Some response of the polymers conductance towards NH3, NO and oxygen was also observed, but with much lower sensitivity than towards HCl. In aqueous solutions, the polymer conductivity was pH dependent; in comparison with 4,4′-dibuthoxy-2,2′-bipyrrole, the conductivity range of the methoxy derivative was shifted to acidic range for about two pH units. A possibility to use the pH dependence for the development of enzymatic biosensors with pH transducing was demonstrated.
KCNJ3 is a new independent prognostic marker for estrogen receptor positive breast cancer patients
(2016)
Numerous studies showed abnormal expression of ion channels in different cancer types. Amongst these, the potassium channel gene KCNJ3 (encoding for GIRK1 proteins) has been reported to be upregulated in tumors of patients with breast cancer and to correlate with positive lymph node status. We aimed to study KCNJ3 levels in different breast cancer subtypes using gene expression data from the TCGA, to validate our findings using RNA in situ hybridization in a validation cohort (GEO ID GSE17705), and to study the prognostic value of KCNJ3using survival analysis. In a total of > 1000 breast cancer patients of two independent data sets we showed a) that KCNJ3 expression is upregulated in tumor tissue compared to corresponding normal tissue (p < 0.001), b) that KCNJ3 expression is associated with estrogen receptor (ER) positive tumors (p < 0.001), but that KCNJ3 expression is variable within this group, and c) that ER positive patients with high KCNJ3 levels have worse overall (p < 0.05) and disease free survival probabilities (p < 0.01), whereby KCNJ3 is an independent prognostic factor (p <0.05). In conclusion, our data suggest that patients with ER positive breast cancer might be stratified into high risk and low risk groups based on the KCNJ3 levels in the tumor.
Mathematical morphology is a part of image processing that has proven to be fruitful for numerous applications. Two main operations in mathematical morphology are dilation and erosion. These are based on the construction of a supremum or infimum with respect to an order over the tonal range in a certain section of the image. The tonal ordering can easily be realised in grey-scale morphology, and some morphological methods have been proposed for colour morphology. However, all of these have certain limitations. In this paper we present a novel approach to colour morphology extending upon previous work in the field based on the Loewner order. We propose to consider an approximation of the supremum by means of a log-sum exponentiation introduced by Maslov. We apply this to the embedding of an RGB image in a field of symmetric 2×2 matrices. In this way we obtain nearly isotropic matrices representing colours and the structural advantage of transitivity. In numerical experiments we highlight some remarkable properties of the proposed approach.
Anonymous communication on the Internet is about hiding the relationship between communicating parties. At NDSS ’16, we presented a new website fingerprinting approach, CUMUL, that utilizes novel features and a simple yet powerful algorithm to attack anonymization networks such as Tor. Based on pattern observation of data flows, this attack aims at identifying the content of encrypted and anonymized connections. Apart from the feature generation and the used classifier, we also provided a large dataset to the research community to study the attack at Internet scale.
In this paper, we emphasize the impact of our artifacts by analyzing publications referring to our work with respect to the dataset, feature extraction method, and source code of the implementation. Based on this data, we draw conclusions about the impact of our artifacts on the research field and discuss their influence on related cybersecurity topics. Overall, from 393 unique citations, we discover more than 130 academic references that utilize our artifacts, 61 among them are highly influential (according to SemanticScholar), and at least 43 are from top-ranked security venues.
This data underlines the significant relevance and impact of our
work as well as of our artifacts in the community and beyond.
In this paper we are concerned with robust structure-preserving denoising filters for color images. We build on a recently proposed transformation from the RGB color space to the space of symmetric 2×2 matrices that has already been used to transfer morphological dilation and erosion concepts from matrix-valued data to color images. We investigate the applicability of this framework to the construction of color-valued median filters. Additionally, we introduce spatial adaptivity into our approach by morphological amoebas that offer excellent capabilities for structure-preserving filtering. Furthermore, we define color-valued amoeba M-smoothers as a generalization of the median-based concepts. Our experiments confirm that all these methods work well with color images. They demonstrate the potential of our approach to define color processing tools based on matrix field techniques.
Für die Analyse von Ausbrüchen von Infektionskrankheiten wie der neuartigen Coronaviruskrankheit COVID-19, die sich über Tröpfchen, Aerosole oder Kontaktinfektion ausbreiten, bietet ein netzwerktheoretischer Ansatz einen besonderen Mehrwert, da eine Ansteckung von einer Person auf die andere notwendigerweise einen direkten Kontakt unter Kopräsenz impliziert und der Ausbruch im größeren Maßstab somit ein Netzwerkmuster aufweist. Neben dem für ein Infektionsgeschehen notwendigen Kontakt zwischen einem infektiösen und einem infizierbaren Individuum gibt es mit dem Ort des Infektionsprozesses allerdings noch eine weitere Variable, die die Rahmenbedingungen bestimmt und von erheblicher Bedeutung sein kann.
Tempo-spatial dynamics of COVID-19 in Germany: A phase model based on a pandemic severity indicator
(2023)
While pandemic waves are often studied on the national scale, they typically are not distributed evenly within countries. This study presents a novel approach to analyzing the spatial-temporal dynamics of the COVID-19 pandemic in Germany. By using a composite indicator of pandemic severity and subdividing the pandemic into fifteen phases, we were able to identify similar trajectories of pandemic severity among all German counties through hierarchical clustering. Our results show that the hotspots and cold spots of the first four waves were relatively stationary in space. This highlights the importance of examining pandemic waves on a regional scale to gain a more comprehensive understanding of their dynamics. By combining spatial autocorrelation and spatial-temporal clustering of time series, we were able to identify important patterns of regional anomalies, which can help target more effective public health interventions on a regional scale.
Quantile filters, or rank-order filters, are local image filters which assign quantiles of intensities of the input image within neighbourhoods as output image values. Combining a multivariate quantile definition developed in matrix-valued morphology with a recently introduced mapping between the RGB colour space and the space of symmetric 2 × 2 matrices, we state a class of colour image quantile filters, along with a class of morphological gradient filters derived from these.We consider variants of these filters based on three matrix norms – the nuclear, Frobenius, and spectral norm – and study their differences. We investigate the properties of the quantile and gradient filters and their links to dilation and erosion operators. Using amoeba structuring elements,we devise image-adaptive versions of our quantile and gradient filters. Experiments are presented to demonstrate the favourable properties of the filters, and compare them to existing approaches in colour morphology.
We hereby present the findings for a new technology to produce portable, flexible, long- term stable and high-resolution sensors and measuring systems for individual lactate value recording in body sweat for regenerative and sports.
A main goal of this study has been the identification of application sites according to body sweat quality and quantity, as well as easy accessibility and handling of the measurement site. For the continuous recording of the lactate value curve with integrated temperature compensation, new types of multifunctional sensor constructions and evaluation algorithms have been developed that can detect and evaluate these parameters precisely and interference-free in real time in body sweat in order to establish a diagnostic correlation with the clinical, therapeutic and sports medicine performance- oriented application scenarios. For this purpose, suitable planar sensor principles have been investigated and a planar sensor was developed. A textile-based sensor suitable for long-term use (several hours to several days of use) has been developed as a braided construction. In particular, a functionalized chitosan layer with a sensitive enzyme and several required electrodes wires have been purposefully used.
Due to a high selectivity, i.e. clear signal interpretation even in the presence of other substances in body sweat, enzymatic measuring systems in an amperometric measure- ment design were primarily investigated. The preferred solution of the developed planar sensor is to be used as a reference sensor for calibration and, together with the preferred solution of the textile sensor, is to be integrated into the demonstrators.
From the intended project results, an immediate direct benefit can be derived for SMEs in the textile manufacturing, finishing and medical products sectors and for the measurement and sensor technology sector.
This paper argues that outbreaks of infectious diseases should be understood as socio‐spatial processes with complex geographies. Considering the different dimensions of space through which an outbreak unfolds, facilitates analysing spatial diffusion of infectious disease in contemporary societies. We attempt to highlight four relevant dimensions of space by applying the TPSN framework to the case of the recent COVID‐19 outbreak in Germany. By identifying key processes of disease diffusion in space, we can explain the spatial patterns of the COVID‐19 outbreak in Germany, which did not feature the well‐known patterns of spatially contagious as in or hierarchical diffusion. In contrast, we find superspreading events and especially relocation diffusion based on existing networks, on which the pathogen travelled like a blind passenger, to be more relevant. For us, these findings prove the value of combining relational thinking with geographic analysis for understanding epidemic outbreaks in contemporary societies.
The arrival of high-mobility two-dimensional materials like graphene leads to the renaissance of former vertical semiconductor–metal–semiconductor (SMS) hot electron transistors. Because of the monolayer thickness of graphene, improved SMS transistors with a semimetallic graphene-base electrode are now feasible for high-frequency applications. In this study we report about a device that consists of amorphous silicon, graphene, and crystalline silicon. For the first time, this device is fabricated by a four-mask lithography process which leads to significant improvements in the device performance. A strongly increased common-emitter current gain of 2% could be achieved while the on–off ratio improved to 1.6 × 105, which is already higher than predicted theoretically. This could be mainly attributed to better interface characteristics and decreased lateral dimensions of the devices. A cutoff frequency of approximately 26 MHz could be forecasted based on the DC measurements of the device.
A graphene-based three terminal barristor device was proposed to overcome the low on/off ratios and insufficient current saturation of conventional graphene field effect transistors. In this study, we fabricated and analyzed a novel graphene-based transistor, which resembles the structure of the barristor but uses a different operating condition. This new device, termed graphene adjustable-barriers transistor (GABT), utilizes a semiconductor-based gate rather than a metal−insulator gate structure to modulate the device currents. The key feature of the device is the two graphene-semiconductor Schottky barriers with different heights that are controlled simultaneously by the gate voltage. Due to the asymmetry of the barriers, the drain current exceeds the gate current by several orders of magnitude. Thus, the GABT can be considered an amplifier with an alterable current gain. In this work, a silicon−graphene−germanium GABT with an ultra-high current gain (ID/IG up to 8 × 106) was fabricated, and the device functionality was demonstrated. Additionally, a capacitance model is applied to predict the theoretical device performance resulting in an on−off ratio above 106, a swing of 87 mV/dec, and a drivecurrent of about 1 × 106 A/cm2.