Article
Refine
Year of publication
Institute
- Fachbereich Medizintechnik und Technomathematik (1316)
- INB - Institut für Nano- und Biotechnologien (485)
- Fachbereich Chemie und Biotechnologie (460)
- Fachbereich Elektrotechnik und Informationstechnik (413)
- IfB - Institut für Bioengineering (392)
- Fachbereich Energietechnik (355)
- Fachbereich Luft- und Raumfahrttechnik (244)
- Fachbereich Maschinenbau und Mechatronik (147)
- Fachbereich Wirtschaftswissenschaften (114)
- Fachbereich Bauingenieurwesen (65)
Has Fulltext
- no (3206) (remove)
Language
- English (3206) (remove)
Document Type
- Article (3206) (remove)
Keywords
- avalanche (5)
- Earthquake (4)
- LAPS (4)
- field-effect sensor (4)
- frequency mixing magnetic detection (4)
- CellDrum (3)
- Heparin (3)
- additive manufacturing (3)
- capacitive field-effect sensor (3)
- hydrogen peroxide (3)
Transgenic plants have the potential to produce recombinant proteins on an agricultural scale, with yields of several tons per year. The cost-effectiveness of transgenic plants increases if simple cultivation facilities such as greenhouses can be used for production. In such a setting, we expressed a novel affinity ligand based on the fluorescent protein DsRed, which we used as a carrier for the linear epitope ELDKWA from the HIV-neutralizing antibody 2F5. The DsRed-2F5-epitope (DFE) fusion protein was produced in 12 consecutive batches of transgenic tobacco (Nicotiana tabacum) plants over the course of 2 years and was purified using a combination of blanching and immobilized metal-ion affinity chromatography (IMAC). The average purity after IMAC was 57 ± 26% (n = 24) in terms of total soluble protein, but the average yield of pure DFE (12 mg kg−1) showed substantial variation (± 97 mg kg−1, n = 24) which correlated with seasonal changes. Specifically, we found that temperature peaks (>28°C) and intense illuminance (>45 klx h−1) were associated with lower DFE yields after purification, reflecting the loss of the epitope-containing C-terminus in up to 90% of the product. Whereas the weather factors were of limited use to predict product yields of individual harvests conducted for each batch (spaced by 1 week), the average batch yields were well approximated by simple linear regression models using two independent variables for prediction (illuminance and plant age). Interestingly, accumulation levels determined by fluorescence analysis were not affected by weather conditions but positively correlated with plant age, suggesting that the product was still expressed at high levels, but the extreme conditions affected its stability, albeit still preserving the fluorophore function. The efficient production of intact recombinant proteins in plants may therefore require adequate climate control and shading in greenhouses or even cultivation in fully controlled indoor farms.
Search for new sequential leptons in e+e- annihilation at petra energies. TASSO Collaboration
(1981)
We conducted a scoping review for active learning in the domain of natural language processing (NLP), which we summarize in accordance with the PRISMA-ScR guidelines as follows:
Objective: Identify active learning strategies that were proposed for entity recognition and their evaluation environments (datasets, metrics, hardware, execution time).
Design: We used Scopus and ACM as our search engines. We compared the results with two literature surveys to assess the search quality. We included peer-reviewed English publications introducing or comparing active learning strategies for entity recognition.
Results: We analyzed 62 relevant papers and identified 106 active learning strategies. We grouped them into three categories: exploitation-based (60x), exploration-based (14x), and hybrid strategies (32x). We found that all studies used the F1-score as an evaluation metric. Information about hardware (6x) and execution time (13x) was only occasionally included. The 62 papers used 57 different datasets to evaluate their respective strategies. Most datasets contained newspaper articles or biomedical/medical data. Our analysis revealed that 26 out of 57 datasets are publicly accessible.
Conclusion: Numerous active learning strategies have been identified, along with significant open questions that still need to be addressed. Researchers and practitioners face difficulties when making data-driven decisions about which active learning strategy to adopt. Conducting comprehensive empirical comparisons using the evaluation environment proposed in this study could help establish best practices in the domain.
Scattering Parameter Measurements of Microstrip Devices using the Double-LNN Calibration Technique
(1994)
Scale braking in inclusive charged particle production by e--e+ annihilation. TASSO Collaboration
(1982)
The concept of energy conversion into platform chemicals using bioelectrochemical systems (BES) has gained increasing attention in recent years, as the technology simultaneously provides an opportunity for sustainable chemical production and tackles the challenge of Power-to-X technologies. There are many approaches to realize the industrial scale of BES. One concept is to equip standard bioreactors with static electrodes. However, large installations resulted in a negative influence on various reactor parameters. In this study, we present a new single-chamber BES based on a stirred tank reactor in which the stirrer was replaced by a carbon fiber brush, performing the functions of the working electrode and the stirrer. The reactor is characterized in abiotic studies and electro-fermentations with Clostridium acetobutylicum. Compared to standard reactors an increase in butanol production of 20.14±3.66 % shows that the new BES can be efficiently used for bioelectrochemical processes.
SAR Simulations & Safety
(2017)
We present an electromechanically coupled computational model for the investigation of a thin cardiac tissue construct consisting of human-induced pluripotent stem cell-derived atrial, ventricular and sinoatrial cardiomyocytes. The mechanical and electrophysiological parts of the finite element model, as well as their coupling are explained in detail. The model is implemented in the open source finite element code Code_Aster and is employed for the simulation of a thin circular membrane deflected by a monolayer of autonomously beating, circular, thin cardiac tissue. Two cardio-active drugs, S-Bay K8644 and veratridine, are applied in experiments and simulations and are investigated with respect to their chronotropic effects on the tissue. These results demonstrate the potential of coupled micro- and macroscopic electromechanical models of cardiac tissue to be adapted to experimental results at the cellular level. Further model improvements are discussed taking into account experimentally measurable quantities that can easily be extracted from the obtained experimental results. The goal is to estimate the potential to adapt the presented model to sample specific cell cultures.
Safety of subjects during radiofrequency exposure in ultra-high-field magnetic resonance imaging
(2020)
Magnetic resonance imaging (MRI) is one of the most important medical imaging techniques. Since the introduction of MRI in the mid-1980s, there has been a continuous trend toward higher static magnetic fields to obtain i.a. a higher signal-to-noise ratio. The step toward ultra-high-field (UHF) MRI at 7 Tesla and higher, however, creates several challenges regarding the homogeneity of the spin excitation RF transmit field and the RF exposure of the subject. In UHF MRI systems, the wavelength of the RF field is in the range of the diameter of the human body, which can result in inhomogeneous spin excitation and local SAR hotspots. To optimize the homogeneity in a region of interest, UHF MRI systems use parallel transmit systems with multiple transmit antennas and time-dependent modulation of the RF signal in the individual transmit channels. Furthermore, SAR increases with increasing field strength, while the SAR limits remain unchanged. Two different approaches to generate the RF transmit field in UHF systems using antenna arrays close and remote to the body are investigated in this letter. Achievable imaging performance is evaluated compared to typical clinical RF transmit systems at lower field strength. The evaluation has been performed under consideration of RF exposure based on local SAR and tissue temperature. Furthermore, results for thermal dose as an alternative RF exposure metric are presented.
The Rothman–Woodroofe symmetry test statistic is revisited on the basis of independent but not necessarily identically distributed random variables. The distribution-freeness if the underlying distributions are all symmetric and continuous is obtained. The results are applied for testing symmetry in a meta-analysis random effects model. The consistency of the procedure is discussed in this situation as well. A comparison with an alternative proposal from the literature is conducted via simulations. Real data are analyzed to demonstrate how the new approach works in practice.
The monolithic scintillator block approach for gamma detection in the Positron Emission Tomography (PET) avoids estimating Depth of Interaction (DOI), reduces dead zones in detector and diminishes costs of detector production. Neural Networks (NN) are very efficient to determine the entrance point of a gamma incident on a scintillator block. This paper presents results on the robustness of the spatial resolution as a function of the random fraction in the data, temperature and HV fluctuations. This is important when implementing the method in a real scanner. Measurements were done with two Hamamatsu S8550 APD arrays, glued on a 20 Ã 20 Ã 10 mm3 monolithic LSO crystal block.
Robust estimators for free surface turbulence characterization: A stepped spillway application
(2020)
Robust estimators are parameters insensitive to the presence of outliers. However, they presume the shape of the variables’ probability density function. This study exemplifies the sensitivity of turbulent quantities to the use of classic and robust estimators and the presence of outliers in turbulent flow depth time series. A wide range of turbulence quantities was analysed based upon a stepped spillway case study, using flow depths sampled with Acoustic Displacement Meters as the flow variable of interest. The studied parameters include: the expected free surface level, the expected fluctuation intensity, the depth skewness, the autocorrelation timescales, the vertical velocity fluctuation intensity, the perturbations celerity and the one-dimensional free surface turbulence spectrum. Three levels of filtering were utilised prior to applying classic and robust estimators, showing that comparable robustness can be obtained either using classic estimators together with an intermediate filtering technique or using robust estimators instead, without any filtering technique.
Using scenarios is vital in identifying and specifying measures for successfully transforming the energy system. Such transformations can be particularly challenging and require the support of a broader set of stakeholders. Otherwise, there will be opposition in the form of reluctance to adopt the necessary technologies. Usually, processes for considering stakeholders' perspectives are very time-consuming and costly. In particular, there are uncertainties about how to deal with modifications in the scenarios. In principle, new consulting processes will be required. In our study, we show how multi-criteria decision analysis can be used to analyze stakeholders' attitudes toward transition paths. Since stakeholders differ regarding their preferences and time horizons, we employ a multi-criteria decision analysis approach to identify which stakeholders will support or oppose a transition path. We provide a flexible template for analyzing stakeholder preferences toward transition paths. This flexibility comes from the fact that our multi-criteria decision aid-based approach does not involve intensive empirical work with stakeholders. Instead, it involves subjecting assumptions to robustness analysis, which can help identify options to influence stakeholders' attitudes toward transitions.
As part of a novel approach to automatic sewer inspection, this paper presents a robust algorithm for automatic flow line detection. A large image repository is obtained from about 50,000 m sewers to represent the high variability of real world sewer systems. Automatic image processing combines Canny edge detection, Hough transform for straight lines and cost minimization using Dijkstra's shortest path algorithm. Assuming that flow lines are mostly smoothly connected horizontal structures, piecewise flow line delineation is reduced to a process of selecting adjacent line candidates. Costs are derived from the gap between adjacent candidates and their reliability. A single parameter α enables simple control of the algorithm. The detected flow line may precisely follow the segmented edges (α = 0.0) or minimize gaps at joints (α = 1.0). Both, manual and ground truth-based analysis indicate that α = 0.8 is optimal and independent of the sewer's material. The algorithm forms an essential step to further automation of sewer inspection.
In this extended abstract we describe the robot programming and planning language READYLOG, a GOLOG dialect which was developed to support the decision making of robots acting in dynamic real-time domains like robotic soccer. The formal framework of READYLOG, which is based on the situation calculus, features imperative control structures like loops and procedures, allows for decision-theoretic planning, and accounts for a continuously changing world. We developed high-level controllers in READYLOG for our soccer robots in RoboCup’s Middle-size league, but also for service robots and for autonomous agents in interactive computer games.
This work demonstrates how the interaction between particle image velocimetry (PIV) and robotics can massively increase measurement efficiency. The interdisciplinary approach is shown using the complex example of an automated, large scale, industrial environment: a typical automotive wind tunnel application. Both the high degree of flexibility in choosing the measurement region and the complete automation of stereo PIV measurements are presented. The setup consists of a combination of three robots, individually used as a 6D traversing unit for the laser illumination system as well as for each of the two cameras. Synchronised movements in the same reference frame are realised through a master-slave setup with a single interface to the user. By integrating the interface into the standard wind tunnel management system, a single measurement plane or a predefined sequence of several planes can be requested through a single trigger event, providing the resulting vector fields within minutes.
In this paper, a brief overview on the demands of large scale industrial PIV and the existing solutions is given. Afterwards, the concept of RoboPIV is introduced as a new approach. In a first step, the usability of a selection of commercially available robot arms is analysed. The challenges of pose uncertainty and importance of absolute accuracy are demonstrated through comparative measurements, explaining the individual pros and cons of the analysed systems. Subsequently, the advantage of integrating RoboPIV directly into the existing wind tunnel management system is shown on basis of a typical measurement sequence. In a final step, a practical measurement procedure, including post-processing, is given by using real data and results. Ultimately, the benefits of high automation are demonstrated, leading to a drastic reduction in necessary measurement time compared to non-automated systems, thus massively increasing the efficiency of PIV measurements.
Risk factors for cardiovascular calcifications in non-diabetic Caucasian haemodialysis patients
(2009)
All cells generate contractile tension. This strain is crucial for mechanically controlling the cell shape, function and survival. In this study, the CellDrum technology quantifying cell's (the cellular) mechanical tension on a pico-scale was used to investigate the effect of lipopolysaccharide (LPS) on human aortic endothelial cell (HAoEC) tension. The LPS effect during gram-negative sepsis on endothelial cells is cell contraction causing endothelium permeability increase. The aim was to finding out whether recombinant activated protein C (rhAPC) would reverse the endothelial cell response in an in-vitro sepsis model. In this study, the established in-vitro sepsis model was confirmed by interleukin 6 (IL-6) levels at the proteomic and genomic levels by ELISA, real time-PCR and reactive oxygen species (ROS) activation by florescence staining. The thrombin cellular contraction effect on endothelial cells was used as a positive control when the CellDrum technology was applied. Additionally, the Ras homolog gene family, member A (RhoA) mRNA expression level was checked by real time-PCR to support contractile tension results. According to contractile tension results, the mechanical predominance of actin stress fibers was a reason of the increased endothelial contractile tension leading to enhanced endothelium contractility and thus permeability enhancement. The originality of this data supports firstly the basic measurement principles of the CellDrum technology and secondly that rhAPC has a beneficial effect on sepsis influenced cellular tension. The technology presented here is promising for future high-throughput cellular tension analysis that will help identify pathological contractile tension responses of cells and prove further cell in-vitro models.
As the field strength and, therefore, the operational frequency in MRI is increased, the wavelength approaches the size of the human head/body, resulting in wave effects, which cause signal decreases and dropouts. Several multichannel approaches have been proposed to try to tackle these problems, including RF shimming, where each element in an array is driven by its own amplifier and modulated with a certain (constant) amplitude and phase relative to the other elements, and Transmit SENSE, where spatially tailored RF pulses are used. In this article, a relatively inexpensive and easy to use imaging scheme for 7 Tesla imaging is proposed to mitigate signal voids due to B1 field inhomogeneity. Two time-interleaved images are acquired using a different excitation mode for each. By forming virtual receive elements, both images are reconstructed together using GRAPPA to achieve a more homogeneous image, with only small SNR and SAR penalty in head and body imaging at 7 Tesla.
Large scale central receiver systems typically deploy between thousands to more than a hundred thousand heliostats. During solar operation, each heliostat is aligned individually in such a way that the overall surface normal bisects the angle between the sun’s position and the aim point coordinate on the receiver. Due to various tracking error sources, achieving accurate alignment ≤1 mrad for all the heliostats with respect to the aim points on the receiver without a calibration system can be regarded as unrealistic. Therefore, a calibration system is necessary not only to improve the aiming accuracy for achieving desired flux distributions but also to reduce or eliminate spillage. An overview of current larger-scale central receiver systems (CRS), tracking error sources and the basic requirements of an ideal calibration system is presented. Leading up to the main topic, a description of general and specific terms on the topics heliostat calibration and tracking control clarifies the terminology used in this work. Various figures illustrate the signal flows along various typical components as well as the corresponding monitoring or measuring devices that indicate or measure along the signal (or effect) chain. The numerous calibration systems are described in detail and classified in groups. Two tables allow the juxtaposition of the calibration methods for a better comparison. In an assessment, the advantages and disadvantages of individual calibration methods are presented.
Germany is a frontrunner in setting frameworks for the transition to a low-carbon system. The mobility sector plays a significant role in this shift, affecting different people and groups on multiple levels. Without acceptance from these stakeholders, emission targets are out of reach. This research analyzes how the heterogeneous preferences of various stakeholders align with the transformation of the mobility sector, looking at the extent to which the German transformation paths are supported and where stakeholders are located.
Under the research objective of comparing stakeholders' preferences to identify which car segments require additional support for a successful climate transition, a status quo of stakeholders and car performance criteria is the foundation for the analysis. Stakeholders' hidden preferences hinder the derivation of criteria weightings from stakeholders; therefore, a ranking from observed preferences is used. This study's inverse multi-criteria decision analysis means that weightings can be predicted and used together with a recalibrated performance matrix to explore future preferences toward car segments.
Results show that stakeholders prefer medium-sized cars, with the trend pointing towards the increased potential for alternative propulsion technologies and electrified vehicles. These insights can guide the improved targeting of policy supporting the energy and mobility transformation. Additionally, the method proposed in this work can fully handle subjective approaches while incorporating a priori information. A software implementation of the proposed method completes this work and is made publicly available.