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Paper des Monats
- ja (20)
The environmental fate of the frequently used broad-spectrum β-lactam antibiotic amoxicillin (AMX) is of high concern regarding the potential evolution of antimicrobial resistance (AMR). Moreover, it is known that AMX is prone to hydrolysis, yielding a variety of hydrolysis products (HPs) with yet unknown effects. Studies to identify those HPs and investigate their formation mechanisms have been reported but a long-term study on their stability in real water samples was missing. In this regard, we investigated the hydrolysis of AMX at two concentration levels in four distinct water types under three different storage conditions over two months. Concentrations of AMX and four relevant HPs were monitored by an LC-MS/MS method revealing pronounced differences in the hydrolysis rate of AMX in tap water and mineral water on the one hand (fast) and surface water on the other(slow). In this context, the occurrence, relative intensities, and stability of certain HPs are more dependent on the water type than on the storage condition. As clarified by ICP-MS, the main difference between the water types was the content of the metals copper and zinc which are supposed to catalyze AMX hydrolysis demonstrating an effective method to degrade AMX at ambient conditions.
The attenuation of wave amplitudes is ruled by the planar, cylindrical or spherical geometry of the wave front (the geometric or power-law attenuation) but also by the damping of the soil (an exponential attenuation). Several low- and high-frequency filter effects are derived for the layering and the damping of the soil, for the moving static and the distributed train loads and for a homogeneous or randomly heterogeneous soil. Measurements of hammer- and train-induced vibrations at five sites have been analysed for these attenuation and filter effects. The measured attenuation with distance can be discribed by generalised power laws and some reasons will be discussed. The theoretical filter effects can well be found in the measurements.
Winkler, Nicolas P. ; Kotlyar, O. ; Schaffernicht, E. ; Fan, H. ; Matsukura, H. ; Ishida, H. ; Neumann, Patrick P. ; Lilienthal, A. J.
To better understand the dynamics in hazardous environments, gas distribution mapping aims to map the gas concentration levels of a specified area precisely. Sampling is typically carried out in a spatially sparse manner, either with a mobile robot or a sensor network and concentration values between known data points have to be interpolated. In this paper, we investigate sequential deep learning models that are able to map the gas distribution based on a multiple time step input from a sensor network. We propose a novel hybrid convolutional LSTM - transpose convolutional structure that we train with synthetic gas distribution data. Our results show that learning the spatial and temporal correlation of gas plume patterns outperforms a non-sequential neural network model.
Simulating a Gas Source Localization Algorithm with Gas Dispersion Produced by Recorded Outdoor Wind
(2023)
This paper reports the use of the first gas dispersion simulator capable of introducing large wind fluctuations into simulations. The proposed simulator enables testing of a modification made to a gas source localization algorithm in a realistic scenario in order to study how the change affects it. Gas source localization in an outdoor environment is a challenging task mainly due to the complexity of the gas spread caused by the unpredictable nature of constantly changing wind. Therefore, a novel use of outdoor wind in developing a gas source localization system by simulation is presented in this paper. To consider the characteristic of sudden but large and unpredictable changes in wind direction, we propose to use recorded outdoor wind to simulate a realistic outdoor gas dispersion which has been done for the first time to the best of our knowledge. With the use of this simulator, we have tested a modification to a mobile robot-based gas source localization algorithm. Multiple simulations of the modified and the original particle filter-based algorithm have been done to study the effect of the tested modification. The results showed that a small difference in the algorithm can greatly impact the results. From this study, we show that the use of simulation consisting of the necessary traits to evaluate outdoor gas source localization, has the potential to accelerate the development of a reliable localization system.
The ISO 16000-6 standard gives directions to adapt the analysis of volatile organic compounds (VOCs) in indoor and test chamber air to very volatile organic compounds (VVOCs). The same techniques with sorbent-based active sampling, thermal desorption and gas chromatography coupled with mass spectrometry (TD-GC/MS) should be used. However, VVOCs require gaseous standards, an adapted GC column and a reliable sampling adsorbent. This work presents experimental results to tackle those three experimental gaps. A stable standard gas mixture containing 47 VVOCs, 13 VOCs and an internal standard was successfully generated. It was employed to study the suitability of seven types of chromatography columns. The use of PLOT (Porous Layer Open Tubular) columns such as PoraBOND Q is well suitable for VVOC analysis. The recoveries of the 60 analytes on a total of 16 adsorbents and their combinations were determined: A combination of the graphitized carbon black Carbograph 5TD 40/60 and the carbon molecular sieve CarbosieveTM SII showed great recoveries for all analytes. Carbon molecular sieves adsorb water which can impair the analysis. A dry purge of the multi-sorbent in the sampling direction led to a complete water removal and promising recoveries of the analytes.
Sergievskaya, A. ; Absil, R. ; Chauvin, A. ; Yusenko, Kirill ; Vesely, J. ; Godfroid, T. ; Konsstantinidis, S.
This paper reports on the effect of the solvent viscosity on the formation of gold nanoparticles (Au NPs) during Sputtering onto Liquid (SoL) process. All other parameters related to the plasma and the host liquid are kept constant. SoL is a simple highly reproducible approach for preparation of colloidal dispersions of small naked NPs. The properties of the final product are determined by both the sputtering parameters and the host liquid characteristics. As a model system we chose to sputter a gold target by a direct-current magnetron discharge onto a line of polymerized rapeseed oils having similar surface tension (32.6 ― 33.1 mJ·m-2 at RT). It was found that well dispersed Au NPs grow in the bulk solution of oils with low viscosities (below 630 cP at 25 °C) while gold films form onto the surface of high viscosity liquids (more than 1000 cP at 25 °C). The mean diameter of the individual Au NPs slightly increases with oil viscosity and is in range about 2.1―2.5 nm according to transmission electron microscopy.
Khrapov, D. ; Paveleva, A. ; Kozadayeva, M. ; Evsevleev, Sergei ; Mishurova, Tatiana ; Bruno, Giovanni ; Surmenev, R. ; Koptyug, A. ; Surmeneva, M.
Electron Beam Powder Bed Fusion-manufactured (E-PBF) porous components with narrow pores or channels and rough walls or struts can be filled with trapped powder after the manufacturing process. Adequate powder removal procedures are required, especially for high-density porous structures. In the present research, sheetbased porous structures with different thicknesses based on triply periodic minimal surfaces fabricated by EPBF were subjected to different post-processing methods, including a traditional powder recovery system for EPBF, chemical etching and ultrasound vibration-assisted powder removal. Wall thickness, internal defects, microstructure and morphology features, powder distribution inside the specimens, mechanical properties and deformation modes were investigated. A powder recovery system could not remove all residual powder from dense structures. In turn, chemical etching was effective for surface morphology changes and subsurface layers elimination but not for powder removal, as it affected the wall thickness, considerably influencing the mechanical properties of the whole structure. The ultrasound vibration method was quite effective for the removal of residual powder from sheet-based TMPS structures and without a severe degradation of mechanical properties. 10.1016/j.msea.2022.144479 Ultrasound vibration also caused grain refinement.
In this study, we explored the detection of weak bonds (WBs) due to contamination and faulty curing (FC) using linear ultrasound and machine learning. For this purpose, aluminium single-lap adhesive joints containing three variants of bonding quality were investigated: perfect bond, WB due to release agent (RA) contamination, and WB due to FC. The data, according to the deviation of the bonding protocol, were arranged in two groups, creating two datasets: distinct and complete. Each dataset included all bonding conditions (perfect, RA, and FC), although the distinct dataset contained only marginal cases, which were expected to be well separable, whereas the complete dataset included data with minor deviations from the bonding protocol. Pulse-echo C-scan images were acquired for all prepared samples in the immersion tank, and 45 features were initially extracted from the time traces representing each bonding group. The initial data were analysed via a t-test and pairwise correlation analysis to reveal statistically significant features. Then, we performed dimensionality reduction using tree-based, recursive, sequential, and linear discriminant analysis (LDA) feature selectors to explore feature importance and classification accuracy with different feature subsets. Finally, the important features identified with the different feature selectors were fed to support vector machine (SVM) classifiers, and the classification accuracies were compared amongst the different feature subsets. The classification accuracy using a distinct dataset in some cases demonstrated nearly 99% accuracy, indicating that significant bonding protocol deviations could be easily detected. It was demonstrated that classification accuracy increased with the number of features. However, even in the case of the 2D feature space obtained using linear discriminant analysis, the bonding quality classification accuracy remained higher than 84%. The feature subspace reduction with LDA demonstrated sufficient classification accuracy and an improvement of nearly 40% in training time compared with that for the initial feature set. Thus, the classical ultrasonic pulse-echo C-scan with an LDA feature transformation and SVM classifier could be used to identify the deviations in the bonding protocol in aluminium single-lap adhesive joints.
This paper presents an erosion interpretation of cohesive granular materials stressed by an impinging jet based on the results of a micromechanical simulation model. The numerical techniques are briefly described, relying on a two-dimensional Lattice Boltzmann Method coupled with a Discrete Element Methods including a simple model of solid intergranular cohesion.
These are then used to perform a parametric study of a planar jet in the laminar regime impinging the surface of granular samples with different degrees of cohesive strength. The results show the pertinence of using a generalized form of the Shields criterion for the quantification of the erosion threshold, which is valid for cohesionless samples, through empirical calibration, and also for cohesive ones. Furthermore, the scouring kinetics are analysed here from the perspective of a selfsimilar expansion of the eroded crater leading to the identification of a characteristic erosion time and the quantification of the classical erosion coefficient. However, the presented results also challenge the postulate of a local erosion law including erodibility parameters as intrinsic material properties. The paper then reviews the main limitations of the simulation and current interpretation models, and discusses the potential causes for the observed discrepancies, questioning the pertinence of using time-averaged macroscopic relations to correctly describe soil erosion. The paper concludes addressing this question with a complementary study of the presented simulations re-assessed at the particle-scale. The resulting local critical shear stress of single grains reveals a very wide dispersion of the data but nevertheless appears to confirm the general macroscopic trend derived for the cohesionless samples, while the introduction of cohesion implies a significant but systematic quantitative deviation between the microscopic and macroscopic estimates. Nevertheless, the micro data still shows consistently that the critical shear stress does actually vary approximately in linear proportion of the adhesive force.
The fungus Botrytis cinerea (Botryotinia fuckeliana) infects more than 500 plant species and causes a wide range of symptoms: soft rots, accompanied by collapse and water-soaking of tissues followed by the appearance of gray masses of conidia on leaves and soft fruits (gray mold), and spots that may turn brown to full-scale soft rotting on flower petals (Botrytis blight). In general, B. cinerea is responsible for severe economic losses that are either due to the damage of growing plants in the field or the rot of harvested fruits, flowers, and vegetables during storage under cold and humid conditions. B. cinerea has adapted to the plant host and its environment by evolving strategies to use plant tissues for proliferation in terms of a necrotrophic lifestyle, and to survive biotic stresses (host responses) as well as abiotic factors of the host’s environment such as sunlight and concomitant stresses. B. cinerea maintains a complex regulatory network of light-sensitive proteins and signal transduction pathways to use light for coordinating stress responses, virulence, and reproduction. Different light-controlled reproduction cycles enable B. cinerea to live in moderate climate zones by infecting and propagating in summer and resting in winter when green host tissues are unavailable.