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Strategies of miniaturised reference electrodes integrated in a silicon-based „one chip“ pH sensor
(2003)
The sterilization of packages in aseptic food processes is highly significant to maintain a consumer-safe product with extended shelf-life. Today, the sterilization of food packages is predominantly accomplished by gaseous hydrogen peroxide (H2O2) in combination with heat. In order to monitor this sterilization process, calorimetric gas sensors as differential set-up of two platinum temperature sensors representing a catalytically active (additionally deposition of MnO2) and a passive segment have been recently developed. The temperature rise of the exothermic decomposition serves as an indicator of the present H2O2 concentration. In the present work, a theoretical approach considering the sensor’s thermochemistry and physical transport phenomena was formulated to evaluate the temperature rise based on the energy content of gaseous H2O2. In a further part of this work, three polymers have been analyzed with respect to their application as passivation materials. The examined polymers are photoresist SU-8, perfluoroalkoxy (PFA) and fluorinated ethylene propylene (FEP). Thermal analyses by means of differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) have been conducted to determine the operation limits of the polymers. The overall chemical resistance and stability of the polymers against the harsh environmental conditions during the sterilization process have been examined by attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR).
When confining pressure is low or absent, extensional fractures are typical, with fractures occurring on unloaded planes in rock. These “paradox” fractures can be explained by a phenomenological extension strain failure criterion. In the past, a simple empirical criterion for fracture initiation in brittle rock has been developed. But this criterion makes unrealistic strength predictions in biaxial compression and tension. A new extension strain criterion overcomes this limitation by adding a weighted principal shear component. The weight is chosen, such that the enriched extension strain criterion represents the same failure surface as the Mohr–Coulomb (MC) criterion. Thus, the MC criterion has been derived as an extension strain criterion predicting failure modes, which are unexpected in the understanding of the failure of cohesive-frictional materials. In progressive damage of rock, the most likely fracture direction is orthogonal to the maximum extension strain. The enriched extension strain criterion is proposed as a threshold surface for crack initiation CI and crack damage CD and as a failure surface at peak P. Examples show that the enriched extension strain criterion predicts much lower volumes of damaged rock mass compared to the simple extension strain criterion.
The treatment method to deactivate viable microorganisms from objects or products is termed sterilization. There are multiple forms of sterilization, each intended to be applied for a specific target, which depends on—but not limited to—the thermal, physical, and chemical stability of that target. Herein, an overview on the currently used sterilization processes in the global market is provided. Different sterilization techniques are grouped under a category that describes the method of treatment: radiation (gamma, electron beam, X-ray, and ultraviolet), thermal (dry and moist heat), and chemical (ethylene oxide, ozone, chlorine dioxide, and hydrogen peroxide). For each sterilization process, the typical process parameters as defined by regulations and the mode of antimicrobial activity are summarized. Finally, the recommended microorganisms that are used as biological indicators to validate sterilization processes in accordance with the rules that are established by various regulatory agencies are summarized.
Sterben und Tod aus wissenschaftlicher Sicht - dying and death from a scientific point of view
(2018)
The optimization of light output and energy resolution of scintillators is of special interest for the development of high resolution and high sensitivity PET. The aim of this work is to obtain statistically reliable results concerning optimal surface treatment of scintillation crystals and the selection of reflector material. For this purpose, raw, mechanically polished and etched LSO crystals (size 2×2×10 mm3) were combined with various reflector materials (Teflon tape, Teflon matrix, BaSO4) and exposed to a 22Na source. In order to ensure the statistical reliability of the results, groups of 10 LSO crystals each were measured for all combinations of surface treatment and reflector material. Using no reflector material the light output increased up to 551±35% by mechanical polishing the surface compared to 100±5% for raw crystals. Etching the surface increased the light output to 441±29%. The untreated crystals had an energy resolution of 24.6±4.0%. By mechanical polishing the surface it was possible to achieve an energy resolution of 13.2±0.8%, by etching of 14.8±0.7%. In combination with BaSO4 as reflector material the maximum increase of light output has been established to 932±57% for mechanically polished and 895±61% for etched crystals. The combination with BaSO4 also caused the best improvement of the energy resolution up to 11.6±0.2% for mechanically polished and 12.2±0.3% for etched crystals. Relating to the light output there was no significant statistical difference between the two surface treatments in combination with BaSO4. In contrast to this, the statistical results of the energy resolution have shown the combination of mechanical polishing and BaSO4 as the optimum.
The paper deals with the asymptotic behaviour of estimators, statistical tests and confidence intervals for L²-distances to uniformity based on the empirical distribution function, the integrated empirical distribution function and the integrated empirical survival function. Approximations of power functions, confidence intervals for the L²-distances and statistical neighbourhood-of-uniformity validation tests are obtained as main applications. The finite sample behaviour of the procedures is illustrated by a simulation study.
Objective
To investigate whether functional brain networks of epilepsy patients treated with antiepileptic medication differ from networks of healthy controls even during the seizure-free interval.
Methods
We applied different rules to construct binary and weighted networks from EEG and MEG data recorded under a resting-state eyes-open and eyes-closed condition from 21 epilepsy patients and 23 healthy controls. The average shortest path length and the clustering coefficient served as global statistical network characteristics.
Results
Independent on the behavioral condition, epileptic brains exhibited a more regular functional network structure. Similarly, the eyes-closed condition was characterized by a more regular functional network structure in both groups. The amount of network reorganization due to behavioral state changes was similar in both groups. Consistent findings could be achieved for networks derived from EEG but hardly from MEG recordings, and network construction rules had a rather strong impact on our findings.
Conclusions
Despite the locality of the investigated processes epileptic brain networks differ in their global characteristics from non-epileptic brain networks. Further methodological developments are necessary to improve the characterization of disturbed and normal functional networks.
Significance
An increased regularity and a diminished modulation capability appear characteristic of epileptic brain networks.
The progress in natural language processing (NLP) research over the last years, offers novel business opportunities for companies, as automated user interaction or improved data analysis. Building sophisticated NLP applications requires dealing with modern machine learning (ML) technologies, which impedes enterprises from establishing successful NLP projects. Our experience in applied NLP research projects shows that the continuous integration of research prototypes in production-like environments with quality assurance builds trust in the software and shows convenience and usefulness regarding the business goal. We introduce STAMP 4 NLP as an iterative and incremental process model for developing NLP applications. With STAMP 4 NLP, we merge software engineering principles with best practices from data science. Instantiating our process model allows efficiently creating prototypes by utilizing templates, conventions, and implementations, enabling developers and data scientists to focus on the business goals. Due to our iterative-incremental approach, businesses can deploy an enhanced version of the prototype to their software environment after every iteration, maximizing potential business value and trust early and avoiding the cost of successful yet never deployed experiments.
In this work, a spore-based biosensor is evaluated to monitor the microbicidal efficacy of sterilization processes applying gaseous hydrogen peroxide (H2O2). The sensor is based on interdigitated electrode structures (IDEs) that have been fabricated by means of thin-film technologies. Impedimetric measurements are applied to study the effect of sterilization process on spores of Bacillus atrophaeus. This resilient microorganism is commonly used in industry to proof the sterilization efficiency. The sensor measurements are accompanied by conventional microbiological challenge tests, as well as morphological characterizations with scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The sensor measurements are correlated with the microbiological test routines. In both methods, namely the sensor-based and microbiological one, a tailing effect has been observed. The results are evaluated and discussed in a three-dimensional calibration plot demonstrating the sensor's suitability to enable a rapid process decision in terms of a successfully performed sterilization.
At the present time, one of the most serious environmental problems of Central Asia and South Kazakhstan is the ongoing large-scale deterioration of principal urban tree populations. Several major centers of massive spread of invasive plant pests have been found in urban dendroflora of this region. The degree of damage of seven most wide-spread aboriginal tree species was found to range from 21.4±1.1 to 85.4±1.8%. In particular, the integrity of the native communities of sycamore (Platanus spp.), willow (Salix spp.), poplar (Populus spp.) and elm (Ulmus spp.) is highly endangered. Our taxonomic analysis of the most dangerous tree pests of the region has revealed them as neobiontic xylophilous insects such as Cossus cossus L. (Order: Lepidoptera L.) Monochamus urussovi Fisch., Monochamus sutor L., Acanthocinus aedelis L. and Ñetonia aureate L. (Order: Coleoptera L.). We relate the origin of this threatening trend with the import of industrial wood in the mid 90s of the last century that was associated with high degree of the constructional work in the region. Because of the absence of efficient natural predators of the pest species, the application of microbiological methods of the pest control and limitation is suggested.
The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis. Automated speaker attribution, which detects who said what to whom in a speech event and is closely related to semantic role labeling, is an important processing step for computational text analysis. We study the potential of the large language model family Llama 2 to automate speaker attribution in German parliamentary debates from 2017-2021. We fine-tune Llama 2 with QLoRA, an efficient training strategy, and observe our approach to achieve competitive performance in the GermEval 2023 Shared Task On Speaker Attribution in German News Articles and Parliamentary Debates. Our results shed light on the capabilities of large language models in automating speaker attribution, revealing a promising avenue for computational analysis of political discourse and the development of semantic role labeling systems.
Recently, the SHARP Corporation, Japan, has developed the world’s first "Plasma Cluster Ions (PCI)" air purification technology using plasma discharge to generate cluster ions. The new plasma cluster device releases positive and negative ions into the air, which are able to decompose and deactivate harmful airborne substances by chemical reactions. Because cluster ions consist of positive and negative ions that normally exist in the natural world, they are completely harmless and safe to humans. The amount of ozone generated by cluster ions is less than 0.01 ppm, which is significantly less than the 0.05-ppm standard for industrial operations and consumer electronics. This amount, thus, has no harming effects whatsoever on the human body. But particular properties and chemical processes in PCI treatment are still under study. It has been shown that PCI in most cases show strongly pronounced irreversible killing effects in respect of airborne microflora due to free-radical induced reactions and can be considered as a potent technology to disinfect both home, medical and industrial appliances.
There is a very large number of very important situations which can be modeled with nonlinear parabolic partial differential equations (PDEs) in several dimensions. In general, these PDEs can be solved by discretizing in the spatial variables and transforming them into huge systems of ordinary differential equations (ODEs), which are very stiff. Therefore, standard explicit methods require a large number of iterations to solve stiff problems. But implicit schemes are computationally very expensive when solving huge systems of nonlinear ODEs. Several families of Extrapolated Stabilized Explicit Runge-Kutta schemes (ESERK) with different order of accuracy (3 to 6) are derived and analyzed in this work. They are explicit methods, with stability regions extended, along the negative real semi-axis, quadratically with respect to the number of stages s, hence they can be considered to solve stiff problems much faster than traditional explicit schemes. Additionally, they allow the adaptation of the step length easily with a very small cost.
Two new families of ESERK schemes (ESERK3 and ESERK6) are derived, and analyzed, in this work. Each family has more than 50 new schemes, with up to 84.000 stages in the case of ESERK6. For the first time, we also parallelized all these new variable step length and variable number of stages algorithms (ESERK3, ESERK4, ESERK5, and ESERK6). These parallelized strategies allow to decrease times significantly, as it is discussed and also shown numerically in two problems. Thus, the new codes provide very good results compared to other well-known ODE solvers. Finally, a new strategy is proposed to increase the efficiency of these schemes, and it is discussed the idea of combining ESERK families in one code, because typically, stiff problems have different zones and according to them and the requested tolerance the optimum order of convergence is different.
Soft Materials in Technology and Biology – Characteristics, Properties, and Parameter Identification
(2008)
Socio-technical scenarios for energy-intensive industries: the future of steel production in Germany
(2019)
Smoothed Finite Element Methods for Nonlinear Solid Mechanics Problems: 2D and 3D Case Studies
(2016)
The Smoothed Finite Element Method (SFEM) is presented as an edge-based and a facebased techniques for 2D and 3D boundary value problems, respectively. SFEMs avoid shortcomings of the standard Finite Element Method (FEM) with lower order elements such as overly stiff behavior, poor stress solution, and locking effects. Based on the idea of averaging spatially the standard strain field of the FEM over so-called smoothing domains SFEM calculates the stiffness matrix for the same number of degrees of freedom (DOFs) as those of the FEM. However, the SFEMs significantly improve accuracy and convergence even for distorted meshes and/or nearly incompressible materials.
Numerical results of the SFEMs for a cardiac tissue membrane (thin plate inflation) and an artery (tension of 3D tube) show clearly their advantageous properties in improving accuracy particularly for the distorted meshes and avoiding shear locking effects.
Stand 01.01.2022 sind in Deutschland 618.460 elektrisch angetriebene KFZ zugelassen. Insgesamt sind derzeit 48.540.878 KFZ zugelassen, was einer Elektromobilitätsquote von ca. 1,2 % entspricht. Derzeit werden Elektromobile über Ladestationen oder Steckdosen mit dem Stromnetz verbunden und üblicherweise mit der vollen Ladekapazität des Anschlusses aufgeladen, bis das Batteriemanagementsystem des Fahrzeugs abhängig vom Ladezustand der Batterie die Ladeleistung reduziert.
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.
Simultaneous detection of cyanide and heavy metals for environmental analysis by means of µISEs
(2010)
In positron emission tomography improving time, energy and spatial detector resolutions and using Compton kinematics introduces the possibility to reconstruct a radioactivity distribution image from scatter coincidences, thereby enhancing image quality. The number of single scattered coincidences alone is in the same order of magnitude as true coincidences. In this work, a compact Compton camera module based on monolithic scintillation material is investigated as a detector ring module. The detector interactions are simulated with Monte Carlo package GATE. The scattering angle inside the tissue is derived from the energy of the scattered photon, which results in a set of possible scattering trajectories or broken line of response. The Compton kinematics collimation reduces the number of solutions. Additionally, the time of flight information helps localize the position of the annihilation. One of the questions of this investigation is related to how the energy, spatial and temporal resolutions help confine the possible annihilation volume. A comparison of currently technically feasible detector resolutions (under laboratory conditions) demonstrates the influence on this annihilation volume and shows that energy and coincidence time resolution have a significant impact. An enhancement of the latter from 400 ps to 100 ps leads to a smaller annihilation volume of around 50%, while a change of the energy resolution in the absorber layer from 12% to 4.5% results in a reduction of 60%. The inclusion of single tissue-scattered data has the potential to increase the sensitivity of a scanner by a factor of 2 to 3 times. The concept can be further optimized and extended for multiple scatter coincidences and subsequently validated by a reconstruction algorithm.
The interest in PET detectors with monolithic block scintillators is growing. In order to obtain high spatial resolutions dedicated positioning algorithms are required. But even an ideal algorithm can only deliver information which is provided by the detector. In this simulation study we investigated the light distribution on one surface of cuboid LSO scintillators of different size. Scintillators with a large aspect ratio (small footprint and large height) showed significant position information only for a minimum interaction depth of the gamma particle. The results allow a quantitative estimate for a useful aspect ratio.
We present an electromechanically coupled Finite Element model for cardiac tissue. It bases on the mechanical model for cardiac tissue of Hunter et al. that we couple to the McAllister-Noble-Tsien electrophysiological model of purkinje fibre cells. The corresponding system of ordinary differential equations is implemented on the level of the constitutive equations in a geometrically and physically nonlinear version of the so-called edge-based smoothed FEM for plates. Mechanical material parameters are determined from our own pressure-deflection experimental setup. The main purpose of the model is to further examine the experimental results not only on mechanical but also on electrophysiological level down to ion channel gates. Moreover, we present first drug treatment simulations and validate the model with respect to the experiments.