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The optical performance of a 2-axis solar concentrator was simulated with the COMSOL Multiphysics® software. The concentrator consists of a mirror array, which was created using the application builder. The mirror facets are preconfigured to form a focal point. During tracking all mirrors are moved simultaneously in a coupled mode by 2 motors in two axes, in order to keep the system in focus with the moving sun. Optical errors on each reflecting surface were implemented in combination with the solar angular cone of ± 4.65 mrad. As a result, the intercept factor of solar radiation that is available to the receiver was calculated as a function of the transversal and longitudinal angles of incidence. In addition, the intensity distribution on the receiver plane was calculated as a function of the incidence angles.
Exposure to prolonged periods in microgravity is associated with deconditioning of the musculoskeletal system due to chronic changes in mechanical stimulation. Given astronauts will operate on the Lunar surface for extended periods of time, it is critical to quantify both external (e.g., ground reaction forces) and internal (e.g., joint reaction forces) loads of relevant movements performed during Lunar missions. Such knowledge is key to predict musculoskeletal deconditioning and determine appropriate exercise countermeasures associated with extended exposure to hypogravity.
Monte Carlo Tree Search (MCTS) is a search technique that in the last decade emerged as a major breakthrough for Artificial Intelligence applications regarding board- and video-games. In 2016, AlphaGo, an MCTS-based software agent, outperformed the human world champion of the board game Go. This game was for long considered almost infeasible for machines, due to its immense search space and the need for a long-term strategy. Since this historical success, MCTS is considered as an effective new approach for many other scientific and technical problems. Interestingly, civil structural engineering, as a discipline, offers many tasks whose solution may benefit from intelligent search and in particular from adopting MCTS as a search tool. In this work, we show how MCTS can be adapted to search for suitable solutions of a structural engineering design problem. The problem consists of choosing the load-bearing elements in a reference reinforced concrete structure, so to achieve a set of specific dynamic characteristics. In the paper, we report the results obtained by applying both a plain and a hybrid version of single-agent MCTS. The hybrid approach consists of an integration of both MCTS and classic Genetic Algorithm (GA), the latter also serving as a term of comparison for the results. The study’s outcomes may open new perspectives for the adoption of MCTS as a design tool for civil engineers.
In the present work, a novel method for monitoring sterilisation processes with gaseous H2O2 in combination with heat activation by means of a specially designed calorimetric gas sensor was evaluated. Therefore, the sterilisation process was extensively studied by using test specimens inoculated with Bacillus atrophaeus spores in order to identify the most influencing process factors on its microbicidal effectiveness. Besides the contact time of the test specimens with gaseous H2O2 varied between 0.2 and 0.5 s, the present H2O2 concentration in a range from 0 to 8% v/v (volume percent) had a strong influence on the microbicidal effectiveness, whereas the change of the vaporiser temperature, gas flow and humidity were almost negligible. Furthermore, a calorimetric H2O2 gas sensor was characterised in the sterilisation process with gaseous H2O2 in a wide range of parameter settings, wherein the measurement signal has shown a linear response against the H2O2 concentration with a sensitivity of 4.75 °C/(% v/v). In a final step, a correlation model by matching the measurement signal of the gas sensor with the microbial inactivation kinetics was established that demonstrates its suitability as an efficient method for validating the microbicidal effectiveness of sterilisation processes with gaseous H2O2.
Designing novel or optimizing existing biodegradable polymers for biomedical applications requires numerous tests on the effect of substances on the degradation process. In the present work, polymer-modified electrolyte–insulator–semiconductor (PMEIS) sensors have been applied for monitoring an enzymatically catalyzed degradation of polymers for the first time. The thin films of biodegradable polymer poly(d,l-lactic acid) and enzyme lipase were used as a model system. During degradation, the sensors were read-out by means of impedance spectroscopy. In order to interpret the data obtained from impedance measurements, an electrical equivalent circuit model was developed. In addition, morphological investigations of the polymer surface have been performed by means of in situ atomic force microscopy. The sensor signal change, which reflects the progress of degradation, indicates an accelerated degradation in the presence of the enzyme compared to hydrolysis in neutral pH buffer media. The degradation rate increases with increasing enzyme concentration. The obtained results demonstrate the potential of PMEIS sensors as a very promising tool for in situ and real-time monitoring of degradation of polymers.
Cell-based sensors for the detection of gases have long been underrepresented, due to the cellular requirement of being cultured in a liquid environment. In this work we established a cell-based gas biosensor for the detection of toxic substances in air, by adapting a commercial sensor chip (Bionas®), previously used for the measurement of pollutants in liquids. Cells of the respiratory tract (A549, RPMI 2650, V79), which survive at a gas phase in a natural context, are used as biological receptors. The physiological cell parameters acidification, respiration and morphology are continuously monitored in parallel. Ammonia was used as a highly water-soluble model gas to test the feasibility of the sensor system. Infrared measurements confirmed the sufficiency of the medium draining method. This sensor system provides a basis for many sensor applications such as environmental monitoring, building technology and public security.
Molecular-genetic identification of emerged novel invasive pathogens of Asiatic Elm Ulmus pumila L
(2014)
The dwarf elm Ulmus pumila L. (Ulmaceae) is one of indigenous species of flora in Kazakhstan and forms a basis of dendroflora in virtually all settlements of the region. In the past decade, multiple outbreaks of previously unknown diseases of the small-leaved elm have been registered. In our study, by the molecular-genetic analysis it was found that the pathogens responsible for the outbreaks are microfungi belonging to the genus Fusarium – F. solani and F. oxysporum. The nucleotide sequences (ITS regions) isolated from the diseased trees showed very high similarity with the GenBank control numbers EU625403.1 and FJ478128.1 (100.0 and 99.0 % respectively). Oncoming research will focus on the search of natural microbial antagonists of the discovered phytopathogens.
Molecular Modeling Approach to the Prediction of Mechanical Properties of Silica-Reinforced Rubbers
(2014)
Recently, we have suggested a nanomechanical model for dissipative loss in filled elastomer networks in the context of the Payne effect. The mechanism is based on a total interfiller particle force exhibiting an intermittent loop, due to the combination of short-range repulsion and dispersion forces with a long-range elastic attraction. The sum of these forces leads, under external strain, to a spontaneous instability of “bonds” between the aggregates in a filler network and attendant energy dissipation. Here, we use molecular dynamics simulations to obtain chemically realistic forces between surface modified silica particles. The latter are combined with the above model to estimate the loss modulus and the low strain storage modulus in elastomers containing the aforementioned filler-compatibilizer systems. The model is compared to experimental dynamic moduli of silica filled rubbers. We find good agreement between the model predictions and the experiments as function of the compatibilizer's molecular structure and its bulk concentration.
Modulation of muscle-tendon interaction in the human triceps surae during an energy dissipation task
(2017)
After menopause, decreased levels of estrogen and progesterone remodel the collagen of the soft tissues thereby reducing their stiffness. Stress urinary incontinence is associated with involuntary urine leakage due to pathological movement of the pelvic organs resulting from lax suspension system, fasciae, and ligaments. This study compares the changes in the orientation and position of the female pelvic organs due to weakened fasciae, ligaments, and their combined laxity. A mixture theory weighted by respective volume fraction of elastin-collagen fibre compound (5%), adipose tissue (85%), and smooth muscle (5%) is adopted to characterize the mechanical behaviour of the fascia. The load carrying response (other than the functional response to the pelvic organs) of each fascia component, pelvic organs, muscles, and ligaments are assumed to be isotropic, hyperelastic, and incompressible. Finite element simulations are conducted during Valsalva manoeuvre with weakened tissues modelled by reduced tissue stiffness. A significant dislocation of the urethrovesical junction is observed due to weakness of the fascia (13.89 mm) compared to the ligaments (5.47 mm). The dynamics of the pelvic floor observed in this study during Valsalva manoeuvre is associated with urethral-bladder hypermobility, greater levator plate angulation, and positive Q-tip test which are observed in incontinent females.
The highly polymorphic human cytochrome P450 2D6 enzyme is involved in the metabolism of up to 25% of all marketed drugs and accounts for significant individual differences in response to CYP2D6 substrates. Because of the differences in the multiplicity and substrate specificity of CYP2D family members among species, it is difficult to predict pathways of human CYP2D6-dependent drug metabolism on the basis of animal studies. To create animal models that reflect the human situation more closely and that allow an in vivo assessment of the consequences of differential CYP2D6 drug metabolism, we have developed a novel straightforward approach to delete the entire murine Cyp2d gene cluster and replace it with allelic variants of human CYP2D6. By using this approach, we have generated mouse lines expressing the two frequent human protein isoforms CYP2D6.1 and CYP2D6.2 and an as yet undescribed variant of this enzyme, as well as a Cyp2d cluster knockout mouse. We demonstrate that the various transgenic mouse lines cover a wide spectrum of different human CYP2D6 metabolizer phenotypes. The novel humanization strategy described here provides a robust approach for the expression of different CYP2D6 allelic variants in transgenic mice and thus can help to evaluate potential CYP2D6-dependent interindividual differences in drug response in the context of personalized medicine.
Modeling contribution to risk assessment of thermal production power for geothermal reservoirs
(2013)
Due to the Renewable Energy Act, in Germany it is planned to increase the amount of renewable energy carriers up to 60%. One of the main problems is the fluctuating supply of wind and solar energy. Here biogas plants provide a solution, because a demand-driven supply is possible. Before running such a plant, it is necessary to simulate and optimize the process. This paper provides a new model of a biogas plant, which is as accurate as the standard ADM1 model. The advantage compared to ADM1 is that it is based on only four parameters compared to 28. Applying this model, an optimization was installed, which allows a demand-driven supply by biogas plants. Finally the results are confirmed by several experiments and measurements with a real test plant.