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Fields of asymmetric tensors play an important role in many applications such as medical imaging (diffusion tensor magnetic resonance imaging), physics, and civil engineering (for example Cauchy-Green-deformation tensor, strain tensor with local rotations, etc.). However, such asymmetric tensors are usually symmetrized and then further processed. Using this procedure results in a loss of information. A new method for the processing of asymmetric tensor fields is proposed restricting our attention to tensors of second-order given by a 2x2 array or matrix with real entries. This is achieved by a transformation resulting in Hermitian matrices that have an eigendecomposition similar to symmetric matrices. With this new idea numerical results for real-world data arising from a deformation of an object by external forces are given. It is shown that the asymmetric part indeed contains valuable information.
A 2-dimensional detector system for high resolution thyroid I-131 scintigraphy was developed. It has a sensitive area of 4 cm×4 cm and consists of a lead-collimator and an array of 10×10 EGO crystals combined with a position sensitive photomultiplier. The spatial resolution and the sensitivity of the detector has been measured and compared to two commercially available gamma-cameras. Furthermore first patient measurements have been carried out
Reinigungsprozesse in der Lebensmittelindustrie. Entwicklung eines Demonstrators zur Überwachung
(2017)
A New Class of Biosensors Based on Tobacco Mosaic Virus and Coat Proteins as Enzyme Nanocarrier
(2016)
The conjunction of (bio-)chemical recognition elements with nanoscale biological building blocks such as virus particles is considered as a very promising strategy for the creation of biohybrids opening novel opportunities for label-free biosensing. This work presents a new approach for the development of biosensors using tobacco mosaic virus (TMV) nanotubes or coat proteins (CPs) as enzyme nanocarriers. Sensor chips combining an array of Pt electrodes loaded with glucose oxidase (GOD)-modified TMV nanotubes or CP aggregates were used for amperometric detection of glucose as a model system for the first time. The presence of TMV nanotubes or CPs on the sensor surface allows binding of a high amount of precisely positioned enzymes without substantial loss of their activity, and may also ensure accessibility of their active centers for analyte molecules. Specific and efficient immobilization of streptavidin-conjugated GOD ([SA]-GOD) complexes on biotinylated TMV nanotubes or CPs was achieved via bioaffinity binding. These layouts were tested in parallel with glucose sensors with adsorptively immobilized [SA]-GOD, as well as [SA]-GOD crosslinked with glutardialdehyde, and came out to exhibit superior sensor performance. The achieved results underline a great potential of an integration of virus/biomolecule hybrids with electronic transducers for future applications in biosensorics and biochips.
Planar and three-dimensional (3D) interdigitated electrodes (IDE) with electrode digits separated by an insulating barrier of different heights were electrochemically characterized and compared in terms of their sensing properties. Due to the impact of the surface resistance, both types of IDE structures display a non-linear behavior in low-ionic strength solutions. The experimental data were fitted to an electrical equivalent circuit and interpreted taking into account the surface-charge-governed properties. The effect of a charged polyelectrolyte layer electrostatically assembled onto the sensor surface on the surface resistance in solutions with different KCl concentration is studied. In case of the same electrode footprint, 3D-IDEs show a larger cell constant and a higher sensitivity to molecular adsorption than that of planar IDEs. The obtained results demonstrate the potential of 3D-IDEs as a new transducer structure for a direct label-free sensing of charged molecules.
In diesem Beitrag werden Ergebnisse der Entwicklung eines modularen festkörperbasierten Sensorsystems für die Überwachung von Zellkulturfermentationen präsentiert. Zur Messung der Elektrolytleitfähigkeit wurde das Layout von Interdigitalelektroden angepasst, um in vergleichsweise gut leitenden Elektrolyten zu messen. Durch Quervernetzung von Glucose-Oxidase mit Glutaraldehyd und Immobilisierung auf einer Platinelektrode wurde ein amperometrischer Glucosesensor mit einem linearen Messbereich von bis zu 2 mM und einer Sensitivität von 168 nA/mM realisiert.
A microfluidic chip integrating amperometric enzyme sensors for the detection of glucose, glutamate and glutamine in cell-culture fermentation processes has been developed. The enzymes glucose oxidase, glutamate oxidase and glutaminase were immobilized by means of cross-linking with glutaraldehyde on platinum thin-film electrodes integrated within a microfluidic channel. The biosensor chip was coupled to a flow-injection analysis system for electrochemical characterization of the sensors. The sensors have been characterized in terms of sensitivity, linear working range and detection limit. The sensitivity evaluated from the respective peak areas was 1.47, 3.68 and 0.28 μAs/mM for the glucose, glutamate and glutamine sensor, respectively. The calibration curves were linear up to a concentration of 20 mM glucose and glutamine and up to 10 mM for glutamate. The lower detection limit amounted to be 0.05 mM for the glucose and glutamate sensor, respectively, and 0.1 mM for the glutamine sensor. Experiments in cell-culture medium have demonstrated a good correlation between the glutamate, glutamine and glucose concentrations measured with the chip-based biosensors in a differential-mode and the commercially available instrumentation. The obtained results demonstrate the feasibility of the realized microfluidic biosensor chip for monitoring of bioprocesses.
Two types of microvalves based on temperature-responsive poly(N-isopropylacrylamide) (PNIPAAm) and pH-responsive poly(sodium acrylate) (PSA) hydrogel films have been developed and tested. The PNIPAAm and PSA hydrogel films were prepared by means of in situ photopolymerization directly inside the fluidic channel of a microfluidic chip fabricated by combining Si and SU-8 technologies. The swelling/shrinking properties and height changes of the PNIPAAm and PSA films inside the fluidic channel were studied at temperatures of deionized water from 14 to 36 °C and different pH values (pH 3–12) of Titrisol buffer, respectively. Additionally, in separate experiments, the lower critical solution temperature (LCST) of the PNIPAAm hydrogel was investigated by means of a differential scanning calorimetry (DSC) and a surface plasmon resonance (SPR) method. Mass-flow measurements have shown the feasibility of the prepared hydrogel films to work as an on-chip integrated temperature- or pH-responsive microvalve capable to switch the flow channel on/off.
Messenger apps like WhatsApp or Telegram are an integral part of daily communication. Besides the various positive effects, those services extend the operating range of criminals. Open trading groups with many thousand participants emerged on Telegram. Law enforcement agencies monitor suspicious users in such chat rooms. This research shows that text analysis, based on natural language processing, facilitates this through a meaningful domain overview and detailed investigations. We crawled a corpus from such self-proclaimed black markets and annotated five attribute types products, money, payment methods, user names, and locations. Based on each message a user sends, we extract and group these attributes to build profiles. Then, we build features to cluster the profiles. Pretrained word vectors yield better unsupervised clustering results than current
state-of-the-art transformer models. The result is a semantically meaningful high-level overview of the user landscape of black market chatrooms. Additionally, the extracted structured information serves as a foundation for further data exploration, for example, the most active users or preferred payment methods.
Messenger apps like WhatsApp and Telegram are frequently used for everyday communication, but they can also be utilized as a platform for illegal activity. Telegram allows public groups with up to 200.000 participants. Criminals use these public groups for trading illegal commodities and services, which becomes a concern for law enforcement agencies, who manually monitor suspicious activity in these chat rooms. This research demonstrates how natural language processing (NLP) can assist in analyzing these chat rooms, providing an explorative overview of the domain and facilitating purposeful analyses of user behavior. We provide a publicly available corpus of annotated text messages with entities and relations from four self-proclaimed black market chat rooms. Our pipeline approach aggregates the extracted product attributes from user messages to profiles and uses these with their sold products as features for clustering. The extracted structured information is the foundation for further data exploration, such as identifying the top vendors or fine-granular price analyses. Our evaluation shows that pretrained word vectors perform better for unsupervised clustering than state-of-the-art transformer models, while the latter is still superior for sequence labeling.
A multi-sensor system is a chemical sensor system which quantitatively and qualitatively records gases with a combination of cross-sensitive gas sensor arrays and pattern recognition software. This paper addresses the issue of data analysis for identification of gases in a gas sensor array. We introduce a software tool for gas sensor array configuration and simulation. It concerns thereby about a modular software package for the acquisition of data of different sensors. A signal evaluation algorithm referred to as matrix method was used specifically for the software tool. This matrix method computes the gas concentrations from the signals of a sensor array. The software tool was used for the simulation of an array of five sensors to determine gas concentration of CH4, NH3, H2, CO and C2H5OH. The results of the present simulated sensor array indicate that the software tool is capable of the following: (a) identify a gas independently of its concentration; (b) estimate the concentration of the gas, even if the system was not previously exposed to this concentration; (c) tell when a gas concentration exceeds a certain value. A gas sensor data base was build for the configuration of the software. With the data base one can create, generate and manage scenarios and source files for the simulation. With the gas sensor data base and the simulation software an on-line Web-based version was developed, with which the user can configure and simulate sensor arrays on-line.
Orthodontic treatments are concomitant with mechanical forces and thereby cause teeth movements. The applied forces are transmitted to the tooth root and the periodontal ligaments which is compressed on one side and tensed up on the other side. Indeed, strong forces can lead to tooth root resorption and the crown-to-tooth ratio is reduced with the potential for significant clinical impact. The cementum, which covers the tooth root, is a thin mineralized tissue of the periodontium that connects the periodontal ligament with the tooth and is build up by cementoblasts. The impact of tension and compression on these cells is investigated in several in vivo and in vitro studies demonstrating differences in protein expression and signaling pathways. In summary, osteogenic marker changes indicate that cyclic tensile forces support whereas static tension inhibits cementogenesis. Furthermore, cementogenesis experiences the same protein expression changes in static conditions as static tension, but cyclic compression leads to the exact opposite of cyclic tension. Consistent with marker expression changes, the singaling pathways of Wnt/ß-catenin and RANKL/OPG show that tissue compression leads to cementum degradation and tension forces to cementogenesis. However, the cementum, and in particular its cementoblasts, remain a research area which should be explored in more detail to understand the underlying mechanism of bone resorption and remodeling after orthodontic treatments.
Design, evaluation and comparison of endorectal coils for hybrid MR-PET imaging of the prostate
(2020)
Prostate cancer is one of the most common cancers among men and its early detection is critical for its successful treatment. The use of multimodal imaging, such as MR-PET, is most advantageous as it is able to provide detailed information about the prostate. However, as the human prostate is flexible and can move into different positions under external conditions, it is important to localise the focused region-of-interest using both MRI and PET under identical circumstances. In this work, we designed five commonly used linear and quadrature radiofrequency surface coils suitable for hybrid MR-PET use in endorectal applications. Due to the endorectal design and the shielded PET insert, the outer face of the coils investigated was curved and the region to be imaged was outside the volume of the coil. The tilting angles of the coils were varied with respect to the main magnetic field direction. This was done to approximate the various positions from which the prostate could be imaged. The transmit efficiencies and safety excitation efficiencies from simulations, together with the signal-to-noise ratios from the MR images were calculated and analysed. Overall, it was found that the overlapped loops driven in quadrature were superior to the other types of coils we tested. In order to determine the effect of the different coil designs on PET, transmission scans were carried out, and it was observed that the differences between attenuation maps with and without the coils were negligible. The findings of this work can provide useful guidance for the integration of such coil designs into MR-PET hybrid systems in the future.
MultiChannel Photomultipliers (PM), like the R7600-00-M64 or R5900-00-M64 from Hamamatsu, are often chosen as photodetectors in high-resolution positron emission tomography (PET). A major problem of this PM is the nonuniform channel gain. In order to solve this problem, light attenuating masks were created. The aim of the masks is a homogenization of the output of all 64 channels using different hole sizes at the channel positions. The hole area, which is individually defined for the different channels, is inversely proportional to the channel gain. The measurements by inserting light attenuating masks improved a homogenization to a ratio of 1:1.2.
Purpose
In vivo, a loss of mesh porosity triggers scar tissue formation and restricts functionality. The purpose of this study was to evaluate the properties and configuration changes as mesh deformation and mesh shrinkage of a soft mesh implant compared with a conventional stiff mesh implant in vitro and in a porcine model.
Material and Methods
Tensile tests and digital image correlation were used to determine the textile porosity for both mesh types in vitro. A group of three pigs each were treated with magnetic resonance imaging (MRI) visible conventional stiff polyvinylidene fluoride meshes (PVDF) or with soft thermoplastic polyurethane meshes (TPU) (FEG Textiltechnik mbH, Aachen, Germany), respectively. MRI was performed with a pneumoperitoneum at a pressure of 0 and 15 mmHg, which resulted in bulging of the abdomen. The mesh-induced signal voids were semiautomatically segmented and the mesh areas were determined. With the deformations assessed in both mesh types at both pressure conditions, the porosity change of the meshes after 8 weeks of ingrowth was calculated as an indicator of preserved elastic properties. The explanted specimens were examined histologically for the maturity of the scar (collagen I/III ratio).
Results
In TPU, the in vitro porosity increased constantly, in PVDF, a loss of porosity was observed under mild stresses. In vivo, the mean mesh areas of TPU were 206.8 cm2 (± 5.7 cm2) at 0 mmHg pneumoperitoneum and 274.6 cm2 (± 5.2 cm2) at 15 mmHg; for PVDF the mean areas were 205.5 cm2 (± 8.8 cm2) and 221.5 cm2 (± 11.8 cm2), respectively. The pneumoperitoneum-induced pressure increase resulted in a calculated porosity increase of 8.4% for TPU and of 1.2% for PVDF. The mean collagen I/III ratio was 8.7 (± 0.5) for TPU and 4.7 (± 0.7) for PVDF.
Conclusion
The elastic properties of TPU mesh implants result in improved tissue integration compared to conventional PVDF meshes, and they adapt more efficiently to the abdominal wall. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 827–833, 2018.
We consider the numerical approximation of second-order semi-linear parabolic stochastic partial differential equations interpreted in the mild sense which we solve on general two-dimensional domains with a C² boundary with homogeneous Dirichlet boundary conditions. The equations are driven by Gaussian additive noise, and several Lipschitz-like conditions are imposed on the nonlinear function. We discretize in space with a spectral Galerkin method and in time using an explicit Euler-like scheme. For irregular shapes, the necessary Dirichlet eigenvalues and eigenfunctions are obtained from a boundary integral equation method. This yields a nonlinear eigenvalue problem, which is discretized using a boundary element collocation method and is solved with the Beyn contour integral algorithm. We present an error analysis as well as numerical results on an exemplary asymmetric shape, and point out limitations of the approach.
Edge-based and face-based smoothed finite element methods (ES-FEM and FS-FEM, respectively) are modified versions of the finite element method allowing to achieve more accurate results and to reduce sensitivity to mesh distortion, at least for linear elements. These properties make the two methods very attractive. However, their implementation in a standard finite element code is nontrivial because it requires heavy and extensive modifications to the code architecture. In this article, we present an element-based formulation of ES-FEM and FS-FEM methods allowing to implement the two methods in a standard finite element code with no modifications to its architecture. Moreover, the element-based formulation permits to easily manage any type of element, especially in 3D models where, to the best of the authors' knowledge, only tetrahedral elements are used in FS-FEM applications found in the literature. Shape functions for non-simplex 3D elements are proposed in order to apply FS-FEM to any standard finite element.
Impaired cerebral autoregulation and neurovascular coupling (NVC) contribute to delayed cerebral ischemia after subarachnoid hemorrhage (SAH). Retinal vessel analysis (RVA) allows non-invasive assessment of vessel dimension and NVC hereby demonstrating a predictive value in the context of various neurovascular diseases. Using RVA as a translational approach, we aimed to assess the retinal vessels in patients with SAH. RVA was performed prospectively in 24 patients with acute SAH (group A: day 5–14), in 11 patients 3 months after ictus (group B: day 90 ± 35), and in 35 age-matched healthy controls (group C). Data was acquired using a Retinal Vessel Analyzer (Imedos Systems UG, Jena) for examination of retinal vessel dimension and NVC using flicker-light excitation. Diameter of retinal vessels—central retinal arteriolar and venular equivalent—was significantly reduced in the acute phase (p < 0.001) with gradual improvement in group B (p < 0.05). Arterial NVC of group A was significantly impaired with diminished dilatation (p < 0.001) and reduced area under the curve (p < 0.01) when compared to group C. Group B showed persistent prolonged latency of arterial dilation (p < 0.05). Venous NVC was significantly delayed after SAH compared to group C (A p < 0.001; B p < 0.05). To our knowledge, this is the first clinical study to document retinal vasoconstriction and impairment of NVC in patients with SAH. Using non-invasive RVA as a translational approach, characteristic patterns of compromise were detected for the arterial and venous compartment of the neurovascular unit in a time-dependent fashion. Recruitment will continue to facilitate a correlation analysis with clinical course and outcome.
We present the novel concept of a combined drilling and melting probe for subsurface ice research. This probe, named “IceMole”, is currently developed, built, and tested at the FH Aachen University of Applied Sciences’ Astronautical Laboratory. Here, we describe its first prototype design and report the results of its field tests on the Swiss Morteratsch glacier. Although the IceMole design is currently adapted to terrestrial glaciers and ice shields, it may later be modified for the subsurface in-situ investigation of extraterrestrial ice, e.g., on Mars, Europa, and Enceladus. If life exists on those bodies, it may be present in the ice (as life can also be found in the deep ice of Earth).
Superparamagnetic iron oxide nanoparticles (SPION) are extensively used for magnetic resonance imaging (MRI) and magnetic particle imaging (MPI), as well as for magnetic fluid hyperthermia (MFH). We here describe a sequential centrifugation protocol to obtain SPION with well-defined sizes from a polydisperse SPION starting formulation, synthesized using the routinely employed co-precipitation technique. Transmission electron microscopy, dynamic light scattering and nanoparticle tracking analyses show that the SPION fractions obtained upon size-isolation are well-defined and almost monodisperse. MRI, MPI and MFH analyses demonstrate improved imaging and hyperthermia performance for size-isolated SPION as compared to the polydisperse starting mixture, as well as to commercial and clinically used iron oxide nanoparticle formulations, such as Resovist® and Sinerem®. The size-isolation protocol presented here may help to identify SPION with optimal properties for diagnostic, therapeutic and theranostic applications.
LAPS are field-effect-based potentiometric sensors which are able to monitor analyte concentrations in a spatially resolved manner. Hence, a LAPS sensor system is a powerful device to record chemical imaging of the concentration of chemical species in an aqueous solution, chemical reactions, or the growth of cell colonies on the sensor surface, to record chemical images. In this work, multi-chamber 3D-printed structures made out of polymer (PP-ABS) were combined with LAPS chips to analyse differentially and simultaneously the metabolic activity of Escherichia coli K12 and Chinese hamster ovary (CHO) cells, and the responds of those cells to the addition of glucose solution.
LAPS-based monitoring of metabolic responses of bacterial cultures in a paper fermentation broth
(2020)
As an alternative renewable energy source, methane production in biogas plants is gaining more and more attention. Biomass in a bioreactor contains different types of microorganisms, which should be considered in terms of process-stability control. Metabolically inactive microorganisms within the fermentation process can lead to undesirable, time-consuming and cost-intensive interventions. Hence, monitoring of the cellular metabolism of bacterial populations in a fermentation broth is crucial to improve the biogas production, operation efficiency, and sustainability. In this work, the extracellular acidification of bacteria in a paper-fermentation broth is monitored after glucose uptake, utilizing a differential light-addressable potentiometric sensor (LAPS) system. The LAPS system is loaded with three different model microorganisms (Escherichia coli, Corynebacterium glutamicum, and Lactobacillus brevis) and the effect of the fermentation broth at different process stages on the metabolism of these bacteria is studied. In this way, different signal patterns related to the metabolic response of microorganisms can be identified. By means of calibration curves after glucose uptake, the overall extracellular acidification of bacterial populations within the fermentation process can be evaluated.
Monitoring the cellular metabolism of bacteria in (bio)fermentation processes is crucial to control and steer them, and to prevent undesired disturbances linked to metabolically inactive microorganisms. In this context, cell-based biosensors can play an important role to improve the quality and increase the yield of such processes. This work describes the simultaneous analysis of the metabolic behavior of three different types of bacteria by means of a differential light-addressable potentiometric sensor (LAPS) set-up. The study includes Lactobacillus brevis, Corynebacterium glutamicum, and Escherichia coli, which are often applied in fermentation processes in bioreactors. Differential measurements were carried out to compensate undesirable influences such as sensor signal drift, and pH value variation during the measurements. Furthermore, calibration curves of the cellular metabolism were established as a function of the glucose concentration or cell number variation with all three model microorganisms. In this context, simultaneous (bio)sensing with the multi-organism LAPS-based set-up can open new possibilities for a cost-effective, rapid detection of the extracellular acidification of bacteria on a single sensor chip. It can be applied to evaluate the metabolic response of bacteria populations in a (bio)fermentation process, for instance, in the biogas fermentation process.
A light-addressable potentiometric sensor (LAPS) is a field-effect-based potentiometric device, which detects concentration changes of an analyte solution on the sensor surface in a spatially resolved way. It uses a light source to generate electron–hole pairs inside the semiconductor, which are separated in the depletion region due to an applied bias voltage across the sensor structure and hence, a surface-potential-dependent photocurrent can be read out. However, depending on the beam angle of the light source, scattering effects can occur, which influence the recorded signal in LAPS-based differential measurements. To solve this problem, a novel illumination unit based on a field programmable gate array (FPGA) consisting of 16 small-sized tunable infrared laser-diode modules (LDMs) is developed. Due to the improved focus of the LDMs with a beam angle of only 2 mrad, undesirable scattering effects are minimized. Escherichia coli (E. coli) K12 bacteria are used as a test microorganism to study the extracellular acidification on the sensor surface. Furthermore, a salt bridge chamber is built up and integrated with the LAPS system enabling multi-chamber differential measurements with a single Ag/AgCl reference electrode.
On-line monitoring of the metabolic activity of microorganisms involved in intermediate stages of biogas production plays an important role to avoid undesirable “down times” during the biogas production. In order to control this process, an on-chip differential measuring system based on the light-addressable potentiometric sensor (LAPS) principle combined with a 3D-printed multi-chamber structure has been realized. As a test microorganism, Escherichia coli K12 (E. coli K12) were used for cell-based measurements. Multi-chamber structures were developed to determine the metabolic activity of E. coli K12 in suspension for a different number of cells, responding to the addition of a constant or variable amount of glucose concentrations, enabling differential and simultaneous measurements.
A light-addressable potentiometric sensor (LAPS) is a field-effect-based potentiometric sensor with an electrolyte/insulator/semiconductor (EIS) structure, which is able to monitor analyte concentrations of (bio-)chemical species in aqueous solutions in a spatially resolved way. Therefore, it is also an appropriate tool to record 2D-chemical images of concentration variations on the sensor surface. In the present work, two differential, LAPS-based measurement principles are introduced to determine the metabolic activity of Escherichia coli (E. coli) K12 and Chinese hamster ovary (CHO) cells as test microorganisms. Hereby, we focus on i) the determination of the extracellular acidification rate (ΔpH/min) after adding glucose solutions to the cell suspensions; and ii) recording the amplitude increase of the photocurrent (Iph) related to the produced acids from E. coli K12 bacteria and CHO cells on the sensor surface by 2D-chemical imaging. For this purpose, 3D-printed multi-chamber structures were developed and mounted on the planar sensor-chip surface to define four independent compartments, enabling differential measurements with varying cell concentrations. The differential concept allows eliminating unwanted drift effects and, with the four-chamber structures, measurements on the different cell concentrations were performed simultaneously, thus reducing also the overall measuring time.