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Purpose
In the determination of the measurement uncertainty, the GUM procedure requires the building of a measurement model that establishes a functional relationship between the measurand and all influencing quantities. Since the effort of modelling as well as quantifying the measurement uncertainties depend on the number of influencing quantities considered, the aim of this study is to determine relevant influencing quantities and to remove irrelevant ones from the dataset.
Design/methodology/approach
In this work, it was investigated whether the effort of modelling for the determination of measurement uncertainty can be reduced by the use of feature selection (FS) methods. For this purpose, 9 different FS methods were tested on 16 artificial test datasets, whose properties (number of data points, number of features, complexity, features with low influence and redundant features) were varied via a design of experiments.
Findings
Based on a success metric, the stability, universality and complexity of the method, two FS methods could be identified that reliably identify relevant and irrelevant influencing quantities for a measurement model.
Originality/value
For the first time, FS methods were applied to datasets with properties of classical measurement processes. The simulation-based results serve as a basis for further research in the field of FS for measurement models. The identified algorithms will be applied to real measurement processes in the future.
This paper considers a paired data framework and discusses the question of marginal homogeneity of bivariate high-dimensional or functional data. The related testing problem can be endowed into a more general setting for paired random variables taking values in a general Hilbert space. To address this problem, a Cramér–von-Mises type test statistic is applied and a bootstrap procedure is suggested to obtain critical values and finally a consistent test. The desired properties of a bootstrap test can be derived that are asymptotic exactness under the null hypothesis and consistency under alternatives. Simulations show the quality of the test in the finite sample case. A possible application is the comparison of two possibly dependent stock market returns based on functional data. The approach is demonstrated based on historical data for different stock market indices.
Acetoin and diacetyl have a major impact on the flavor of alcoholic beverages such as wine or beer. Therefore, their measurement is important during the fermentation process. Until now, gas chromatographic techniques have typically been applied; however, these require expensive laboratory equipment and trained staff, and do not allow for online monitoring. In this work, a capacitive electrolyte–insulator–semiconductor sensor modified with tobacco mosaic virus (TMV) particles as enzyme nanocarriers for the detection of acetoin and diacetyl is presented. The enzyme acetoin reductase from Alkalihalobacillus clausii DSM 8716ᵀ is immobilized via biotin–streptavidin affinity, binding to the surface of the TMV particles. The TMV-assisted biosensor is electrochemically characterized by means of leakage–current, capacitance–voltage, and constant capacitance measurements. In this paper, the novel biosensor is studied regarding its sensitivity and long-term stability in buffer solution. Moreover, the TMV-assisted capacitive field-effect sensor is applied for the detection of diacetyl for the first time. The measurement of acetoin and diacetyl with the same sensor setup is demonstrated. Finally, the successive detection of acetoin and diacetyl in buffer and in diluted beer is studied by tuning the sensitivity of the biosensor using the pH value of the measurement solution.
Inference on the basis of high-dimensional and functional data are two topics which are discussed frequently in the current statistical literature. A possibility to include both topics in a single approach is working on a very general space for the underlying observations, such as a separable Hilbert space. We propose a general method for consistently hypothesis testing on the basis of random variables with values in separable Hilbert spaces. We avoid concerns with the curse of dimensionality due to a projection idea. We apply well-known test statistics from nonparametric inference to the projected data and integrate over all projections from a specific set and with respect to suitable probability measures. In contrast to classical methods, which are applicable for real-valued random variables or random vectors of dimensions lower than the sample size, the tests can be applied to random vectors of dimensions larger than the sample size or even to functional and high-dimensional data. In general, resampling procedures such as bootstrap or permutation are suitable to determine critical values. The idea can be extended to the case of incomplete observations. Moreover, we develop an efficient algorithm for implementing the method. Examples are given for testing goodness-of-fit in a one-sample situation in [1] or for testing marginal homogeneity on the basis of a paired sample in [2]. Here, the test statistics in use can be seen as generalizations of the well-known Cramérvon-Mises test statistics in the one-sample and two-samples case. The treatment of other testing problems is possible as well. By using the theory of U-statistics, for instance, asymptotic null distributions of the test statistics are obtained as the sample size tends to infinity. Standard continuity assumptions ensure the asymptotic exactness of the tests under the null hypothesis and that the tests detect any alternative in the limit. Simulation studies demonstrate size and power of the tests in the finite sample case, confirm the theoretical findings, and are used for the comparison with concurring procedures. A possible application of the general approach is inference for stock market returns, also in high data frequencies. In the field of empirical finance, statistical inference of stock market prices usually takes place on the basis of related log-returns as data. In the classical models for stock prices, i.e., the exponential Lévy model, Black-Scholes model, and Merton model, properties such as independence and stationarity of the increments ensure an independent and identically structure of the data. Specific trends during certain periods of the stock price processes can cause complications in this regard. In fact, our approach can compensate those effects by the treatment of the log-returns as random vectors or even as functional data.
Cell spraying has become a feasible application method for cell therapy and tissue engineering approaches. Different devices have been used with varying success. Often, twin-fluid atomizers are used, which require a high gas velocity for optimal aerosolization characteristics. To decrease the amount and velocity of required air, a custom-made atomizer was designed based on the effervescent principle. Different designs were evaluated regarding spray characteristics and their influence on human adipose-derived mesenchymal stromal cells. The arithmetic mean diameters of the droplets were 15.4–33.5 µm with decreasing diameters for increasing gas-to-liquid ratios. The survival rate was >90% of the control for the lowest gas-to-liquid ratio. For higher ratios, cell survival decreased to approximately 50%. Further experiments were performed with the design, which had shown the highest survival rates. After seven days, no significant differences in metabolic activity were observed. The apoptosis rates were not influenced by aerosolization, while high gas-to-liquid ratios caused increased necrosis levels. Tri-lineage differentiation potential into adipocytes, chondrocytes, and osteoblasts was not negatively influenced by aerosolization. Thus, the effervescent aerosolization principle was proven suitable for cell applications requiring reduced amounts of supplied air. This is the first time an effervescent atomizer was used for cell processing.
Utilizing an appropriate enzyme immobilization strategy is crucial for designing enzyme-based biosensors. Plant virus-like particles represent ideal nanoscaffolds for an extremely dense and precise immobilization of enzymes, due to their regular shape, high surface-to-volume ratio and high density of surface binding sites. In the present work, tobacco mosaic virus (TMV) particles were applied for the co-immobilization of penicillinase and urease onto the gate surface of a field-effect electrolyte-insulator-semiconductor capacitor (EISCAP) with a p-Si-SiO₂-Ta₂O₅ layer structure for the sequential detection of penicillin and urea. The TMV-assisted bi-enzyme EISCAP biosensor exhibited a high urea and penicillin sensitivity of 54 and 85 mV/dec, respectively, in the concentration range of 0.1–3 mM. For comparison, the characteristics of single-enzyme EISCAP biosensors modified with TMV particles immobilized with either penicillinase or urease were also investigated. The surface morphology of the TMV-modified Ta₂O₅-gate was analyzed by scanning electron microscopy. Additionally, the bi-enzyme EISCAP was applied to mimic an XOR (Exclusive OR) enzyme logic gate.
Bacterial cellulose (BC) is a biopolymer produced by different microorganisms, but in biotechnological practice, Komagataeibacter xylinus is used. The micro- and nanofibrillar structure of BC, which forms many different-sized pores, creates prerequisites for the introduction of other polymers into it, including those synthesized by other microorganisms. The study aims to develop a cocultivation system of BC and prebiotic producers to obtain BC-based composite material with prebiotic activity. In this study, pullulan (PUL) was found to stimulate the growth of the probiotic strain Lactobacillus rhamnosus GG better than the other microbial polysaccharides gellan and xanthan. BC/PUL biocomposite with prebiotic properties was obtained by cocultivation of Komagataeibacter xylinus and Aureobasidium pullulans, BC and PUL producers respectively, on molasses medium. The inclusion of PUL in BC is proved gravimetrically by scanning electron microscopy and by Fourier transformed infrared spectroscopy. Cocultivation demonstrated a composite effect on the aggregation and binding of BC fibers, which led to a significant improvement in mechanical properties. The developed approach for “grafting” of prebiotic activity on BC allows preparation of environmentally friendly composites of better quality.
Electric flight has the potential for a more sustainable and energy-saving way of aviation compared to fossil fuel aviation. The electric motor can be used as a generator inflight to regenerate energy during descent. Three different approaches to regenerating with electric propeller powertrains are proposed in this paper. The powertrain is to be set up in a wind tunnel to determine the propeller efficiency in both working modes as well as the noise emissions. Furthermore, the planned flight tests are discussed. In preparation for these tests, a yaw stability analysis is performed with the result that the aeroplane is controllable during flight and in the most critical failure case. The paper shows the potential for inflight regeneration and addresses the research gaps in the dual role of electric powertrains for propulsion and regeneration of general aviation aircraft.
Direct methods comprising limit and shakedown analysis is a branch of computational mechanics. It plays a significant role in mechanical and civil engineering design. The concept of direct method aims to determinate the ultimate load bearing capacity of structures beyond the elastic range. For practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and onstraints. If strength and loading are random quantities, the problem of shakedown analysis is considered as stochastic programming. This paper presents a method so called chance constrained programming, an effective method of stochastic programming, to solve shakedown analysis problem under random condition of strength. In this our investigation, the loading is deterministic, the strength is distributed as normal or lognormal variables.
With the growing interest in small distributed sensors for the “Internet of Things”, more attention is being paid to energy harvesting techologies. Reducing or eliminating the need for external power sources or batteries make devices more self-sufficient, more reliable, and reduces maintenance requirements. The Wiegand effect is a proven technology for harvesting small amounts of electrical power from mechanical motion.
This work introduces a novel method for the detection of H₂O₂ vapor/aerosol of low concentrations, which is mainly applied in the sterilization of equipment in medical industry. Interdigitated electrode (IDE) structures have been fabricated by means of microfabrication techniques. A differential setup of IDEs was prepared, containing an active sensor element (active IDE) and a passive sensor element (passive IDE), where the former was immobilized with an enzymatic membrane of horseradish peroxidase that is selective towards H₂O₂. Changes in the IDEs’ capacitance values (active sensor element versus passive sensor element) under H₂O₂ vapor/aerosol atmosphere proved the detection in the concentration range up to 630 ppm with a fast response time (<60 s). The influence of relative humidity was also tested with regard to the sensor signal, showing no cross-sensitivity. The repeatability assessment of the IDE biosensors confirmed their stable capacitive signal in eight subsequent cycles of exposure to H₂O₂ vapor/aerosol. Room-temperature detection of H₂O₂ vapor/aerosol with such miniaturized biosensors will allow a future three-dimensional, flexible mapping of aseptic chambers and help to evaluate sterilization assurance in medical industry.
It was generally believed that coal sources are not favorable as live-in habitats for microorganisms due to their recalcitrant chemical nature and negligible decomposition. However, accumulating evidence has revealed the presence of diverse microbial groups in coal environments and their significant metabolic role in coal biogeochemical dynamics and ecosystem functioning. The high oxygen content, organic fractions, and lignin-like structures of lower-rank coals may provide effective means for microbial attack, still representing a greatly unexplored frontier in microbiology. Coal degradation/conversion technology by native bacterial and fungal species has great potential in agricultural development, chemical industry production, and environmental rehabilitation. Furthermore, native microalgal species can offer a sustainable energy source and an excellent bioremediation strategy applicable to coal spill/seam waters. Additionally, the measures of the fate of the microbial community would serve as an indicator of restoration progress on post-coal-mining sites. This review puts forward a comprehensive vision of coal biodegradation and bioprocessing by microorganisms native to coal environments for determining their biotechnological potential and possible applications.
In this study, an online multi-sensing platform was engineered to simultaneously evaluate various process parameters of food package sterilization using gaseous hydrogen peroxide (H₂O₂). The platform enabled the validation of critical aseptic parameters. In parallel, one series of microbiological count reduction tests was performed using highly resistant spores of B. atrophaeus DSM 675 to act as the reference method for sterility validation. By means of the multi-sensing platform together with microbiological tests, we examined sterilization process parameters to define the most effective conditions with regards to the highest spore kill rate necessary for aseptic packaging. As these parameters are mutually associated, a correlation between different factors was elaborated. The resulting correlation indicated the need for specific conditions regarding the applied H₂O₂ gas temperature, the gas flow and concentration, the relative humidity and the exposure time. Finally, the novel multi-sensing platform together with the mobile electronic readout setup allowed for the online and on-site monitoring of the sterilization process, selecting the best conditions for sterility and, at the same time, reducing the use of the time-consuming and costly microbiological tests that are currently used in the food package industry.
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 subtilase family (S8), a member of the clan SB of serine proteases are ubiquitous in all kingdoms of life and fulfil different physiological functions. Subtilases are divided in several groups and especially subtilisins are of interest as they are used in various industrial sectors. Therefore, we searched for new subtilisin sequences of the family Bacillaceae using a data mining approach. The obtained 1,400 sequences were phylogenetically classified in the context of the subtilase family. This required an updated comprehensive overview of the different groups within this family. To fill this gap, we conducted a phylogenetic survey of the S8 family with characterised holotypes derived from the MEROPS database. The analysis revealed the presence of eight previously uncharacterised groups and 13 subgroups within the S8 family. The sequences that emerged from the data mining with the set filter parameters were mainly assigned to the subtilisin subgroups of true subtilisins, high-alkaline subtilisins, and phylogenetically intermediate subtilisins and represent an excellent source for new subtilisin candidates.
An improved and convenient ninhydrin assay for aminoacylase activity measurements was developed using the commercial EZ Nin™ reagent. Alternative reagents from literature were also evaluated and compared. The addition of DMSO to the reagent enhanced the solubility of Ruhemann's purple (RP). Furthermore, we found that the use of a basic, aqueous buffer enhances stability of RP. An acidic protocol for the quantification of lysine was developed by addition of glacial acetic acid. The assay allows for parallel processing in a 96-well format with measurements microtiter plates.
REM sleep without atonia (RSWA) is a key feature for the diagnosis of rapid eye movement (REM) sleep behaviour disorder (RBD). We introduce RBDtector, a novel open-source software to score RSWA according to established SINBAR visual scoring criteria. We assessed muscle activity of the mentalis, flexor digitorum superficialis (FDS), and anterior tibialis (AT) muscles. RSWA was scored manually as tonic, phasic, and any activity by human scorers as well as using RBDtector in 20 subjects. Subsequently, 174 subjects (72 without RBD and 102 with RBD) were analysed with RBDtector to show the algorithm’s applicability. We additionally compared RBDtector estimates to a previously published dataset. RBDtector showed robust conformity with human scorings. The highest congruency was achieved for phasic and any activity of the FDS. Combining mentalis any and FDS any, RBDtector identified RBD subjects with 100% specificity and 96% sensitivity applying a cut-off of 20.6%. Comparable performance was obtained without manual artefact removal. RBD subjects also showed muscle bouts of higher amplitude and longer duration. RBDtector provides estimates of tonic, phasic, and any activity comparable to human scorings. RBDtector, which is freely available, can help identify RBD subjects and provides reliable RSWA metrics.
Atmospheric pressure plasma-jet treatment of PAN-nonwovens—carbonization of nanofiber electrodes
(2022)
Carbon nanofibers are produced from dielectric polymer precursors such as polyacrylonitrile (PAN). Carbonized nanofiber nonwovens show high surface area and good electrical conductivity, rendering these fiber materials interesting for application as electrodes in batteries, fuel cells, and supercapacitors. However, thermal processing is slow and costly, which is why new processing techniques have been explored for carbon fiber tows. Alternatives for the conversion of PAN-precursors into carbon fiber nonwovens are scarce. Here, we utilize an atmospheric pressure plasma jet to conduct carbonization of stabilized PAN nanofiber nonwovens. We explore the influence of various processing parameters on the conductivity and degree of carbonization of the converted nanofiber material. The precursor fibers are converted by plasma-jet treatment to carbon fiber nonwovens within seconds, by which they develop a rough surface making subsequent surface activation processes obsolete. The resulting carbon nanofiber nonwovens are applied as supercapacitor electrodes and examined by cyclic voltammetry and impedance spectroscopy. Nonwovens that are carbonized within 60 s show capacitances of up to 5 F g⁻¹.