TY - JOUR A1 - Monakhova, Yulia A1 - Diehl, Bernd W.K. T1 - Multinuclear NMR screening of pharmaceuticals using standardization by 2H integral of a deuterated solvent JF - Journal of Pharmaceutical and Biomedical Analysis N2 - NMR standardization approach that uses the 2H integral of deuterated solvent for quantitative multinuclear analysis of pharmaceuticals is described. As a proof of principle, the existing NMR procedure for the analysis of heparin products according to US Pharmacopeia monograph is extended to the determination of Na+ and Cl- content in this matrix. Quantification is performed based on the ratio of a 23Na (35Cl) NMR integral and 2H NMR signal of deuterated solvent, D2O, acquired using the specific spectrometer hardware. As an alternative, the possibility of 133Cs standardization using the addition of Cs2CO3 stock solution is shown. Validation characteristics (linearity, repeatability, sensitivity) are evaluated. A holistic NMR profiling of heparin products can now also be used for the quantitative determination of inorganic compounds in a single analytical run using a single sample. In general, the new standardization methodology provides an appealing alternative for the NMR screening of inorganic and organic components in pharmaceutical products. KW - NMR spectroscopy KW - Inorganic ions KW - Heparin KW - Standardization Y1 - 2022 SN - 0731-7085 U6 - https://doi.org/10.1016/j.jpba.2021.114530 VL - 209 IS - Article number: 114530 PB - Elsevier ER - TY - JOUR A1 - Burger, René A1 - Lindner, Simon A1 - Rumpf, Jessica A1 - Do, Xuan Tung A1 - Diehl, Bernd W.K. A1 - Rehahn, Matthias A1 - Monakhova, Yulia A1 - Schulze, Margit T1 - Benchtop versus high field NMR: Comparable performance found for the molecular weight determination of lignin JF - Journal of Pharmaceutical and Biomedical Analysis N2 - Lignin is a promising renewable biopolymer being investigated worldwide as an environmentally benign substitute of fossil-based aromatic compounds, e.g. for the use as an excipient with antioxidant and antimicrobial properties in drug delivery or even as active compound. For its successful implementation into process streams, a quick, easy, and reliable method is needed for its molecular weight determination. Here we present a method using 1H spectra of benchtop as well as conventional NMR systems in combination with multivariate data analysis, to determine lignin’s molecular weight (Mw and Mn) and polydispersity index (PDI). A set of 36 organosolv lignin samples (from Miscanthus x giganteus, Paulownia tomentosa and Silphium perfoliatum) was used for the calibration and cross validation, and 17 samples were used as external validation set. Validation errors between 5.6% and 12.9% were achieved for all parameters on all NMR devices (43, 60, 500 and 600 MHz). Surprisingly, no significant difference in the performance of the benchtop and high-field devices was found. This facilitates the application of this method for determining lignin’s molecular weight in an industrial environment because of the low maintenance expenditure, small footprint, ruggedness, and low cost of permanent magnet benchtop NMR systems. KW - NMR KW - PLS-regression KW - Molecular weight determination KW - Chemometrics KW - Biomass Y1 - 2022 SN - 0731-7085 U6 - https://doi.org/10.1016/j.jpba.2022.114649 VL - 212 IS - Article number: 114649 PB - Elsevier CY - New York, NY ER - TY - JOUR A1 - Monakhova, Yulia A1 - Soboleva, Polina M. A1 - Fedotova, Elena S. A1 - Musina, Kristina T. A1 - Burmistrova, Natalia A. T1 - Quantum chemical calculations of IR spectra of heparin disaccharide subunits JF - Computational and Theoretical Chemistry N2 - Heparin is a natural polysaccharide, which plays essential role in many biological processes. Alterations in building blocks can modify biological roles of commercial heparin products, due to significant changes in the conformation of the polymer chain. The variability structure of heparin leads to difficulty in quality control using different analytical methods, including infrared (IR) spectroscopy. In this paper molecular modelling of heparin disaccharide subunits was performed using quantum chemistry. The structural and spectral parameters of these disaccharides have been calculated using RHF/6-311G. In addition, over-sulphated chondroitin sulphate disaccharide was studied as one of the most widespread contaminants of heparin. Calculated IR spectra were analyzed with respect to specific structure parameters. IR spectroscopic fingerprint was found to be sensitive to substitution pattern of disaccharide subunits. Vibrational assignments of calculated spectra were correlated with experimental IR spectral bands of native heparin. Chemometrics was used to perform multivariate analysis of simulated spectral data. KW - IR spectroscopy KW - Chemometrics KW - Quantum chemistry KW - Molecular modelling KW - Quality control Y1 - 2022 SN - 2210-271X U6 - https://doi.org/10.1016/j.comptc.2022.113891 VL - 1217 IS - Article number: 113891 PB - Elsevier CY - New York, NY ER - TY - JOUR A1 - Mueller, Tobias A1 - Segin, Alexander A1 - Weigand, Christoph A1 - Schmitt, Robert H. T1 - Feature selection for measurement models JF - International journal of quality & reliability management N2 - 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. KW - Feature selection KW - Modelling KW - Measurement models KW - Measurement uncertainty Y1 - 2022 U6 - https://doi.org/10.1108/IJQRM-07-2021-0245 SN - 0265-671X IS - Vol. ahead-of-print, No. ahead-of-print. PB - Emerald Group Publishing Limited CY - Bingley ER - TY - JOUR A1 - Röthenbacher, Annika A1 - Cesari, Matteo A1 - Doppler, Christopher E.J. A1 - Okkels, Niels A1 - Willemsen, Nele A1 - Sembowski, Nora A1 - Seger, Aline A1 - Lindner, Marie A1 - Brune, Corinna A1 - Stefani, Ambra A1 - Högl, Birgit A1 - Bialonski, Stephan A1 - Borghammer, Per A1 - Fink, Gereon R. A1 - Schober, Martin A1 - Sommerauer, Michael T1 - RBDtector: an open-source software to detect REM sleep without atonia according to visual scoring criteria JF - Scientific Reports N2 - 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. Y1 - 2022 U6 - https://doi.org/10.1038/s41598-022-25163-9 SN - 2045-2322 VL - 12 IS - Article number: 20886 SP - 1 EP - 14 PB - Springer Nature CY - London ER - TY - JOUR A1 - Rübbelke, Dirk A1 - Vögele, Stefan A1 - Grajewski, Matthias A1 - Zobel, Luzy T1 - Hydrogen-based steel production and global climate protection: An empirical analysis of the potential role of a European cross border adjustment mechanism JF - Journal of Cleaner Production N2 - The European Union's aim to become climate neutral by 2050 necessitates ambitious efforts to reduce carbon emissions. Large reductions can be attained particularly in energy intensive sectors like iron and steel. In order to prevent the relocation of such industries outside the EU in the course of tightening environmental regulations, the establishment of a climate club jointly with other large emitters and alternatively the unilateral implementation of an international cross-border carbon tax mechanism are proposed. This article focuses on the latter option choosing the steel sector as an example. In particular, we investigate the financial conditions under which a European cross border mechanism is capable to protect hydrogen-based steel production routes employed in Europe against more polluting competition from abroad. By using a floor price model, we assess the competitiveness of different steel production routes in selected countries. We evaluate the climate friendliness of steel production on the basis of specific GHG emissions. In addition, we utilize an input-output price model. It enables us to assess impacts of rising cost of steel production on commodities using steel as intermediates. Our results raise concerns that a cross-border tax mechanism will not suffice to bring about competitiveness of hydrogen-based steel production in Europe because the cost tends to remain higher than the cost of steel production in e.g. China. Steel is a classic example for a good used mainly as intermediate for other products. Therefore, a cross-border tax mechanism for steel will increase the price of products produced in the EU that require steel as an input. This can in turn adversely affect competitiveness of these sectors. Hence, the effects of higher steel costs on European exports should be borne in mind and could require the cross-border adjustment mechanism to also subsidize exports. Y1 - 2022 U6 - https://doi.org/10.1016/j.jclepro.2022.135040 SN - 0959-6526 VL - 380 IS - Part 2, Art. Nr.:135040 PB - Elsevier ER - TY - JOUR A1 - Tran, Ngoc Trinh A1 - Trinh, Tu Luc A1 - Dao, Ngoc Tien A1 - Giap, Van Tan A1 - Truong, Manh Khuyen A1 - Dinh, Thuy Ha A1 - Staat, Manfred T1 - FEM shakedown analysis of structures under random strength with chance constrained programming JF - Vietnam Journal of Mechanics N2 - Direct methods, comprising limit and shakedown analysis, are a branch of computational mechanics. They play a significant role in mechanical and civil engineering design. The concept of direct methods aims to determine the ultimate load carrying capacity of structures beyond the elastic range. In practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and constraints. If strength and loading are random quantities, the shakedown analysis can be formulated as stochastic programming problem. In this paper, a method called chance constrained programming is presented, which is an effective method of stochastic programming to solve shakedown analysis problems under random conditions of strength. In this study, the loading is deterministic, and the strength is a normally or lognormally distributed variable. KW - limit analysis KW - shakedown analysis KW - chance constrained programming KW - stochastic programming KW - reliability of structures Y1 - 2022 U6 - https://doi.org/10.15625/0866-7136/17943 SN - 0866-7136 SN - 2815-5882 VL - 44 IS - 4 SP - 459 EP - 473 PB - Vietnam Academy of Science and Technology (VAST) ER - TY - JOUR A1 - Baringhaus, Ludwig A1 - Gaigall, Daniel T1 - A goodness-of-fit test for the compound Poisson exponential model JF - Journal of Multivariate Analysis N2 - On the basis of bivariate data, assumed to be observations of independent copies of a random vector (S,N), we consider testing the hypothesis that the distribution of (S,N) belongs to the parametric class of distributions that arise with the compound Poisson exponential model. Typically, this model is used in stochastic hydrology, with N as the number of raindays, and S as total rainfall amount during a certain time period, or in actuarial science, with N as the number of losses, and S as total loss expenditure during a certain time period. The compound Poisson exponential model is characterized in the way that a specific transform associated with the distribution of (S,N) satisfies a certain differential equation. Mimicking the function part of this equation by substituting the empirical counterparts of the transform we obtain an expression the weighted integral of the square of which is used as test statistic. We deal with two variants of the latter, one of which being invariant under scale transformations of the S-part by fixed positive constants. Critical values are obtained by using a parametric bootstrap procedure. The asymptotic behavior of the tests is discussed. A simulation study demonstrates the performance of the tests in the finite sample case. The procedure is applied to rainfall data and to an actuarial dataset. A multivariate extension is also discussed. KW - Bootstrapping KW - Collective risk model Y1 - 2022 U6 - https://doi.org/10.1016/j.jmva.2022.105154 SN - 0047-259X SN - 1095-7243 VL - 195 IS - Article 105154 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kaulen, Lars A1 - Schwabedal, Justus T. C. A1 - Schneider, Jules A1 - Ritter, Philipp A1 - Bialonski, Stephan T1 - Advanced sleep spindle identification with neural networks JF - Scientific Reports N2 - Sleep spindles are neurophysiological phenomena that appear to be linked to memory formation and other functions of the central nervous system, and that can be observed in electroencephalographic recordings (EEG) during sleep. Manually identified spindle annotations in EEG recordings suffer from substantial intra- and inter-rater variability, even if raters have been highly trained, which reduces the reliability of spindle measures as a research and diagnostic tool. The Massive Online Data Annotation (MODA) project has recently addressed this problem by forming a consensus from multiple such rating experts, thus providing a corpus of spindle annotations of enhanced quality. Based on this dataset, we present a U-Net-type deep neural network model to automatically detect sleep spindles. Our model’s performance exceeds that of the state-of-the-art detector and of most experts in the MODA dataset. We observed improved detection accuracy in subjects of all ages, including older individuals whose spindles are particularly challenging to detect reliably. Our results underline the potential of automated methods to do repetitive cumbersome tasks with super-human performance. Y1 - 2022 U6 - https://doi.org/10.1038/s41598-022-11210-y SN - 2045-2322 N1 - Corresponding author: Stephan Bialonski VL - 12 IS - Article number: 7686 SP - 1 EP - 10 PB - Springer Nature CY - London ER - TY - JOUR A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - Gamification of virtual reality assembly training: Effects of a combined point and level system on motivation and training results JF - International Journal of Human-Computer Studies N2 - Virtual Reality (VR) offers novel possibilities for remote training regardless of the availability of the actual equipment, the presence of specialists, and the training locations. Research shows that training environments that adapt to users' preferences and performance can promote more effective learning. However, the observed results can hardly be traced back to specific adaptive measures but the whole new training approach. This study analyzes the effects of a combined point and leveling VR-based gamification system on assembly training targeting specific training outcomes and users' motivations. The Gamified-VR-Group with 26 subjects received the gamified training, and the Non-Gamified-VR-Group with 27 subjects received the alternative without gamified elements. Both groups conducted their VR training at least three times before assembling the actual structure. The study found that a level system that gradually increases the difficulty and error probability in VR can significantly lower real-world error rates, self-corrections, and support usages. According to our study, a high error occurrence at the highest training level reduced the Gamified-VR-Group's feeling of competence compared to the Non-Gamified-VR-Group, but at the same time also led to lower error probabilities in real-life. It is concluded that a level system with a variable task difficulty should be combined with carefully balanced positive and negative feedback messages. This way, better learning results, and an improved self-evaluation can be achieved while not causing significant impacts on the participants' feeling of competence. KW - Gamification KW - Virtual reality KW - Assembly KW - User study KW - Level system Y1 - 2022 U6 - https://doi.org/10.1016/j.ijhcs.2022.102854 SN - 1071-5819 VL - 165 IS - Art. No. 102854 PB - Elsevier CY - Amsterdam ER -