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- ItemSharp phase transition for Cox percolation(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2022) Hirsch, Christian; Jahnel, Benedikt; Muirhead, StephenWe prove the sharpness of the percolation phase transition for a class of Cox percolation models, i.e., models of continuum percolation in a random environment. The key requirements are that the environment has a finite range of dependence and satisfies a local boundedness condition, however the FKG inequality need not hold. The proof combines the OSSS inequality with a coarse-graining construction.
- ItemAutomated and rapid identification of multidrug resistant Escherichia coli against the lead drugs of acylureidopenicillins, cephalosporins, and fluoroquinolones using specific Raman marker bands(Weinheim : Wiley-VCH-Verl., 2020) Götz, Theresa; Dahms, Marcel; Kirchhoff, Johanna; Beleites, Claudia; Glaser, Uwe; Bohnert, Jürgen A.; Pletz, Mathias W.; Popp, Jürgen; Schlattmann, Peter; Neugebauer, UteA Raman-based, strain-independent, semi-automated method is presented that allows the rapid (<3 hours) determination of antibiotic susceptibility of bacterial pathogens isolated from clinical samples. Applying a priori knowledge about the mode of action of the respective antibiotic, we identified characteristic Raman marker bands in the spectrum and calculated batch-wise weighted sum scores from standardized Raman intensity differences between spectra of antibiotic exposed and nonexposed samples of the same strains. The lead substances for three relevant antibiotic classes (fluoroquinolone ciprofloxacin, third-generation cephalosporin cefotaxime, ureidopenicillin piperacillin) against multidrug-resistant Gram-negative bacteria (MRGN) revealed a high sensitivity and specificity for the susceptibility testing of two Escherichia coli laboratory strains and 12 clinical isolates. The method benefits from the parallel incubation of control and treated samples, which reduces the variance due to alterations in cultivation conditions and the standardization of differences between batches leading to long-term comparability of Raman measurements. © 2020 The Authors. Journal of Biophotonics published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
- ItemGradient methods for problems with inexact model of the objective(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2020) Stonyakin, Fedor; Dvinskikh, Darina; Dvurechensky, Pavel; Kroshnin, Alexey; Kuznetsova, Olesya; Agafonov, Artem; Gasnikov, Alexander; Tyurin, Alexander; Uribe, Cesar A.; Pasechnyuk, Dmitry; Artamonov, SergeiWe consider optimization methods for convex minimization problems under inexact information on the objective function. We introduce inexact model of the objective, which as a particular cases includes inexact oracle [19] and relative smoothness condition [43]. We analyze gradient method which uses this inexact model and obtain convergence rates for convex and strongly convex problems. To show potential applications of our general framework we consider three particular problems. The first one is clustering by electorial model introduced in [49]. The second one is approximating optimal transport distance, for which we propose a Proximal Sinkhorn algorithm. The third one is devoted to approximating optimal transport barycenter and we propose a Proximal Iterative Bregman Projections algorithm. We also illustrate the practical performance of our algorithms by numerical experiments.
- ItemOptimality conditions for convex stochastic optimization problems in Banach spaces with almost sure state constraint(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2020) Geiersbach, Caroline; Wollner, WinnifriedWe analyze a convex stochastic optimization problem where the state is assumed to belong to the Bochner space of essentially bounded random variables with images in a reflexive and separable Banach space. For this problem, we obtain optimality conditions that are, with an appropriate model, necessary and sufficient. Additionally, the Lagrange multipliers associated with optimality conditions are integrable vector-valued functions and not only measures. A model problem is given demonstrating the application to PDE-constrained optimization under uncertainty.
- ItemAn Innovative Protocol for Metaproteomic Analyses of Microbial Pathogens in Cystic Fibrosis Sputum(Lausanne : Frontiers Media, 2021) Graf, Alexander C.; Striesow, Johanna; Pané-Farré, Jan; Sura, Thomas; Wurster, Martina; Lalk, Michael; Pieper, Dietmar H.; Becher, Dörte; Kahl, Barbara C.; Riedel, KatharinaHallmarks of cystic fibrosis (CF) are increased viscosity of mucus and impaired mucociliary clearance within the airways due to mutations of the cystic fibrosis conductance regulator gene. This facilitates the colonization of the lung by microbial pathogens and the concomitant establishment of chronic infections leading to tissue damage, reduced lung function, and decreased life expectancy. Although the interplay between key CF pathogens plays a major role during disease progression, the pathophysiology of the microbial community in CF lungs remains poorly understood. Particular challenges in the analysis of the microbial population present in CF sputum is (I) the inhomogeneous, viscous, and slimy consistence of CF sputum, and (II) the high number of human proteins masking comparably low abundant microbial proteins. To address these challenges, we used 21 CF sputum samples to develop a reliable, reproducible and widely applicable protocol for sputum processing, microbial enrichment, cell disruption, protein extraction and subsequent metaproteomic analyses. As a proof of concept, we selected three sputum samples for detailed metaproteome analyses and complemented and validated metaproteome data by 16S sequencing, metabolomic as well as microscopic analyses. Applying our protocol, the number of bacterial proteins/protein groups increased from 199-425 to 392-868 in enriched samples compared to nonenriched controls. These early microbial metaproteome data suggest that the arginine deiminase pathway and multiple proteases and peptidases identified from various bacterial genera could so far be underappreciated in their contribution to the CF pathophysiology. By providing a standardized and effective protocol for sputum processing and microbial enrichment, our study represents an important basis for future studies investigating the physiology of microbial pathogens in CF in vivo – an important prerequisite for the development of novel antimicrobial therapies to combat chronic recurrent airway infection in CF.
- ItemNonlinear Optical Investigation of Microbial Chromoproteins(Lausanne : Frontiers Media, 2020) Krekic, Szilvia; Zakar, Tomás; Gombos, Zoltán; Valkai, Sándor; Mero, Mark; Zimányi, László; Heiner, Zsuzsanna; Dér, AndrásMembrane-bound or cytosolic light-sensitive proteins, playing a crucial role in energy- and signal-transduction processes of various photosynthetic microorganisms, have been optimized for sensing or harvesting light by myriads of years of evolution. Upon absorption of a photon, they undergo a usually cyclic reaction series of conformations, and the accompanying spectro-kinetic events assign robust nonlinear optical (NLO) properties for these chromoproteins. During recent years, they have attracted a considerable interest among researchers of the applied optics community as well, where finding the appropriate NLO material for a particular application is a pivotal task. Potential applications have emerged in various branches of photonics, including optical information storage and processing, higher-harmonic and white-light continuum generation, or biosensorics. In our earlier work, we also raised the possibility of using chromoproteins, such as bacteriorhodopsin (bR), as building blocks for the active elements of integrated optical (IO) circuits, where several organic and inorganic photonic materials have been considered as active components, but so far none of them has been deemed ideal for the purpose. In the current study, we investigate the linear and NLO properties of biofilms made of photoactive yellow protein (PYP) and bR. The kinetics of the photoreactions are monitored by time-resolved absorption experiments, while the refractive index of the films and its light-induced changes are measured using the Optical Waveguide Lightmode Spectroscopy (OWLS) and Z-scan techniques, respectively. The nonlinear refractive index and the refractive index change of both protein films were determined in the green spectral range in a wide range of intensities and at various laser repetition rates. The nonlinear refractive index and refractive index change of PYP were compared to those of bR, with respect to photonics applications. Our results imply that the NLO properties of these proteins make them promising candidates for utilization in applied photonics, and they should be considered as valid alternatives for active components of IO circuits. © Copyright © 2020 Krekic, Zakar, Gombos, Valkai, Mero, Zimányi, Heiner and Dér.
- ItemOptimized Deep Learning Model as a Basis for Fast UAV Mapping of Weed Species in Winter Wheat Crops(Basel : MDPI AG, 2021) de Camargo, Tibor; Schirrmann, Michael; Landwehr, Niels; Dammer, Karl-Heinz; Pflanz, MichaelWeed maps should be available quickly, reliably, and with high detail to be useful for site-specific management in crop protection and to promote more sustainable agriculture by reducing pesticide use. Here, the optimization of a deep residual convolutional neural network (ResNet-18) for the classification of weed and crop plants in UAV imagery is proposed. The target was to reach sufficient performance on an embedded system by maintaining the same features of the ResNet-18 model as a basis for fast UAV mapping. This would enable online recognition and subsequent mapping of weeds during UAV flying operation. Optimization was achieved mainly by avoiding redundant computations that arise when a classification model is applied on overlapping tiles in a larger input image. The model was trained and tested with imagery obtained from a UAV flight campaign at low altitude over a winter wheat field, and classification was performed on species level with the weed species Matricaria chamomilla L., Papaver rhoeas L., Veronica hederifolia L., and Viola arvensis ssp. arvensis observed in that field. The ResNet-18 model with the optimized image-level prediction pipeline reached a performance of 2.2 frames per second with an NVIDIA Jetson AGX Xavier on the full resolution UAV image, which would amount to about 1.78 ha h−1 area output for continuous field mapping. The overall accuracy for determining crop, soil, and weed species was 94%. There were some limitations in the detection of species unknown to the model. When shifting from 16-bit to 32-bit model precision, no improvement in classification accuracy was observed, but a strong decline in speed performance, especially when a higher number of filters was used in the ResNet-18 model. Future work should be directed towards the integration of the mapping process on UAV platforms, guiding UAVs autonomously for mapping purpose, and ensuring the transferability of the models to other crop fields.
- ItemConvergence bounds for empirical nonlinear least-squares(Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2020) Eigel, Martin; Trunschke, Philipp; Schneider, ReinholdWe consider best approximation problems in a nonlinear subset of a Banach space of functions. The norm is assumed to be a generalization of the L2 norm for which only a weighted Monte Carlo estimate can be computed. The objective is to obtain an approximation of an unknown target function by minimizing the empirical norm. In the case of linear subspaces it is well-known that such least squares approximations can become inaccurate and unstable when the number of samples is too close to the number of parameters. We review this statement for general nonlinear subsets and establish error bounds for the empirical best approximation error. Our results are based on a restricted isometry property (RIP) which holds in probability and we show sufficient conditions for the RIP to be satisfied with high probability. Several model classes are examined where analytical statements can be made about the RIP. Numerical experiments illustrate some of the obtained stability bounds.
- ItemSimulating second-generation herbaceous bioenergy crop yield using the global hydrological model H08 (v.bio1)(Katlenburg-Lindau : Copernicus, 2020) Ai, Zhipin; Hanasaki, Naota; Heck, Vera; Hasegawa, Tomoko; Fujimori, ShinichiroLarge-scale deployment of bioenergy plantations would have adverse effects on water resources. There is an increasing need to ensure the appropriate inclusion of the bioenergy crops in global hydrological models. Here, through parameter calibration and algorithm improvement, we enhanced the global hydrological model H08 to simulate the bioenergy yield from two dedicated herbaceous bioenergy crops: Miscanthus and switchgrass. Site-specific evaluations showed that the enhanced model had the ability to simulate yield for both Miscanthus and switchgrass, with the calibrated yields being well within the ranges of the observed yield. Independent country-specific evaluations further confirmed the performance of the H08 (v.bio1). Using this improved model, we found that unconstrained irrigation more than doubled the yield under rainfed condition, but reduced the water use efficiency (WUE) by 32 % globally. With irrigation, the yield in dry climate zones can exceed the rainfed yields in tropical climate zones. Nevertheless, due to the low water consumption in tropical areas, the highest WUE was found in tropical climate zones, regardless of whether the crop was irrigated. Our enhanced model provides a new tool for the future assessment of bioenergy–water tradeoffs.
- ItemInactivation of airborne bacteria by plasma treatment and ionic wind for indoor air cleaning(Hoboken, NJ : Wiley Interscience, 2020) Prehn, Franziska; Timmermann, Eric; Kettlitz, Manfred; Schaufler, Katharina; Günther, Sebastian; Hahn, VeronikaAirborne bacteria are a general problem in medical or health care facilities with a high risk for nosocomial infections. Rooms with a continuous airflow, such as operation theaters, are of particular importance due to a possible dissemination and circulation of pathogens including multidrug-resistant microorganisms. In this regard, a cold atmospheric-pressure plasma (CAP) may be a possibility to support usual disinfection procedures due to its decontaminating properties. The aim of this study was to determine the antimicrobial efficacy of a plasma decontamination module that included a dielectric barrier discharge for plasma generation. Experimental parameters such as an airflow velocity of 4.5 m/s and microbial contaminations of approximately 6,000 colony-forming units (cfu)/m3 were used to simulate practical conditions of a ventilation system in an operating theater. The apathogenic microorganism Escherichia coli K12 DSM 11250/NCTC 10538 and the multidrug-resistant strains E. coli 21181 and 21182 (isolated from patients) were tested to determine the antimicrobial efficacy. In summary, the number of cfu was reduced by 31–89% for the tested E. coli strains, whereby E. coli K12 was the most susceptible strain toward inactivation by the designed plasma module. A possible correlation between the number or kind of resistances and susceptibility against plasma was discussed. The inactivation of microorganisms was affected by plasma intensity and size of the plasma treatment area. In addition, the differences of the antimicrobial efficacies caused through the nebulization of microorganisms in front (upstream) or behind (downstream) the plasma source were compared. The presence of ionic wind had no influence on the reduction of the number of cfu for E. coli K12, as the airflow velocity was too high for a successful precipitation, which would be a prerequisite for an increased antimicrobial efficacy. The inactivation of the tested microorganisms confirms the potential of CAP for the improvement of air quality. The scale-up of this model system may provide a novel tool for an effective air cleaning process.