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In this study, we investigate the thermo-mechanical relaxation and crystallization behavior of polyethylene using mesoscale molecular dynamics simulations. Our models specifically mimic constraints that occur in real-life polymer processing: After strong uniaxial stretching of the melt, we quench and release the polymer chains at different loading conditions. These conditions allow for free or hindered shrinkage, respectively. We present the shrinkage and swelling behavior as well as the crystallization kinetics over up to 600 ns simulation time. We are able to precisely evaluate how the interplay of chain length, temperature, local entanglements and orientation of chain segments influences crystallization and relaxation behavior. From our models, we determine the temperature dependent crystallization rate of polyethylene, including crystallization onset temperature.
Introduction: Chronic pain is a frequent severe disease and often associated with anxiety, depression, insomnia, disability, and reduced quality of life. This maladaptive condition is further characterized by sensory loss, hyperalgesia, and allodynia. Blue light has been hypothesized to modulate sensory neurons and thereby influence nociception.
Objectives: Here, we compared the effects of blue light vs red light and thermal control on pain sensation in a human experimental pain model.
Methods: Pain, hyperalgesia, and allodynia were induced in 30 healthy volunteers through high-density transcutaneous electrical stimulation. Subsequently, blue light, red light, or thermal control treatment was applied in a cross-over design. The nonvisual effects of the respective light treatments were examined using a well-established quantitative sensory testing protocol. Somatosensory parameters as well as pain intensity and quality were scored.
Results: Blue light substantially reduced spontaneous pain as assessed by numeric rating scale pain scoring. Similarly, pain quality was significantly altered as assessed by the German counterpart of the McGill Pain Questionnaire. Furthermore, blue light showed antihyperalgesic, antiallodynic, and antihypesthesic effects in contrast to red light or thermal control treatment.
Conclusion: Blue-light phototherapy ameliorates pain intensity and quality in a human experimental pain model and reveals antihyperalgesic, antiallodynic, and antihypesthesic effects. Therefore, blue-light phototherapy may be a novel approach to treat pain in multiple conditions.
Suitability of Current Sensors for the Measurement of Switching Currents in Power Semiconductors
(2021)
This paper investigates the impact of current sensors on the measurement of transient currents in fast-switching power semiconductors in a double pulse test (DPT environment. We review previous research that assesses the influence of current sensors on a DPT circuit through mathematical modeling. The developed selection aids can be used to identify suitable current sensors for transient current measurements of fast-switching power semiconductors and to estimate the error introduced by their insertion into the DPT circuit. Afterwards, this analysis is extended by including further elements from real DPT applications to increase the consistency of the error estimation with practical situations and setups. Both methods are compared and their individual advantages and drawbacks are discussed. Finally, a recommendation on when to use which method is derived.
Animal models are often needed in cancer research but some research questions may be answered with other models, e.g., 3D replicas of patient-specific data, as these mirror the anatomy in more detail. We, therefore, developed a simple eight-step process to fabricate a 3D replica from computer tomography (CT) data using solely open access software and described the method in detail. For evaluation, we performed experiments regarding endoscopic tumor treatment with magnetic nanoparticles by magnetic hyperthermia and local drug release. For this, the magnetic nanoparticles need to be accumulated at the tumor site via a magnetic field trap. Using the developed eight-step process, we printed a replica of a locally advanced pancreatic cancer and used it to find the best position for the magnetic field trap. In addition, we described a method to hold these magnetic field traps stably in place. The results are highly important for the development of endoscopic tumor treatment with magnetic nanoparticles as the handling and the stable positioning of the magnetic field trap at the stomach wall in close proximity to the pancreatic tumor could be defined and practiced. Finally, the detailed description of the workflow and use of open access software allows for a wide range of possible uses.
Different analyses and feasibility studies have been conducted on the plant extracts of thyme (Thymus vulgaris), European horse chestnut (Aesculus hippocastanum), Nordmann fir (Abies nordmanniana), and snowdrop (Galanthus elwesii) to evaluate bio‐based alternatives to common petrol‐based stabilisers. For this purpose, in this study, plant extracts were incorporated into poly‐lactic acid films (PLA) at different concentrations. The films’ UV absorbance and migration into packed food was analysed via photometric assays (ABTS radical cation scavenging capacity assay, β‐carotene assay) and GC–MS analysis. Furthermore, the synergistic antioxidant effects of various combinations of extracts and isolated active compounds were determined. This way, antioxidant effects can be increased, allowing for a highly effective use of resources. All extracts were successfully incorporated into PLA films and showed notable photoabsorbing effects, while no migration risk was observed. Depending on extract combinations, high synergistic effects of up to 726% can be utilised to improve the effectiveness of bio‐based extracts. This applies particularly to tomato paste and Aesculus hippocastanum extracts, which overall show high synergistic and antioxidant effects in combination with each other and with isolated active compounds. The study shows that it is possible to create safe bio‐based antioxidant films which show even improved properties when using highlighted target combinations.
The clear-sky radiative effect of aerosol–radiation interactions is of relevance for our understanding of the climate system. The influence of aerosol on the surface energy budget is of high interest for the renewable energy sector. In this study, the radiative effect is investigated in particular with respect to seasonal and regional variations for the region of Germany and the year 2015 at the surface and top of atmosphere using two complementary approaches.
First, an ensemble of clear-sky models which explicitly consider aerosols is utilized to retrieve the aerosol optical depth and the surface direct radiative effect of aerosols by means of a clear-sky fitting technique. For this, short-wave broadband irradiance measurements in the absence of clouds are used as a basis. A clear-sky detection algorithm is used to identify cloud-free observations. Considered are measurements of the short-wave broadband global and diffuse horizontal irradiance with shaded and unshaded pyranometers at 25 stations across Germany within the observational network of the German Weather Service (DWD). The clear-sky models used are the Modified MAC model (MMAC), the Meteorological Radiation Model (MRM) v6.1, the Meteorological–Statistical solar radiation model (METSTAT), the European Solar Radiation Atlas (ESRA), Heliosat-1, the Center for Environment and Man solar radiation model (CEM), and the simplified Solis model. The definition of aerosol and atmospheric characteristics of the models are examined in detail for their suitability for this approach.
Second, the radiative effect is estimated using explicit radiative transfer simulations with inputs on the meteorological state of the atmosphere, trace gases and aerosol from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis. The aerosol optical properties (aerosol optical depth, Ångström exponent, single scattering albedo and asymmetry parameter) are first evaluated with AERONET direct sun and inversion products. The largest inconsistency is found for the aerosol absorption, which is overestimated by about 0.03 or about 30 % by the CAMS reanalysis. Compared to the DWD observational network, the simulated global, direct and diffuse irradiances show reasonable agreement within the measurement uncertainty. The radiative kernel method is used to estimate the resulting uncertainty and bias of the simulated direct radiative effect. The uncertainty is estimated to −1.5 ± 7.7 and 0.6 ± 3.5 W m−2 at the surface and top of atmosphere, respectively, while the annual-mean biases at the surface, top of atmosphere and total atmosphere are −10.6, −6.5 and 4.1 W m−2, respectively.
The retrieval of the aerosol radiative effect with the clear-sky models shows a high level of agreement with the radiative transfer simulations, with an RMSE of 5.8 W m−2 and a correlation of 0.75. The annual mean of the REari at the surface for the 25 DWD stations shows a value of −12.8 ± 5 W m−2 as the average over the clear-sky models, compared to −11 W m−2 from the radiative transfer simulations. Since all models assume a fixed aerosol characterization, the annual cycle of the aerosol radiation effect cannot be reproduced. Out of this set of clear-sky models, the largest level of agreement is shown by the ESRA and MRM v6.1 models.
This study investigates the effects of four multifunctional chain-extending cross-linkers (CECL) on the processability, mechanical performance, and structure of polybutylene adipate terephthalate (PBAT) and polylactic acid (PLA) blends produced using film blowing technology. The newly developed reference compound (M·VERA® B5029) and the CECL modified blends are characterized with respect to the initial properties and the corresponding properties after aging at 50 °C for 1 and 2 months. The tensile strength, seal strength, and melt volume rate (MVR) are markedly changed after thermal aging, whereas the storage modulus, elongation at the break, and tear resistance remain constant. The degradation of the polymer chains and crosslinking with increased and decreased MVR, respectively, is examined thoroughly with differential scanning calorimetry (DSC), with the results indicating that the CECL-modified blends do not generally endure thermo-oxidation over time. Further, DSC measurements of 25 µm and 100 µm films reveal that film blowing pronouncedly changes the structures of the compounds. These findings are also confirmed by dynamic mechanical analysis, with the conclusion that tris(2,4-di-tert-butylphenyl)phosphite barely affects the glass transition temperature, while with the other changes in CECL are seen. Cross-linking is found for aromatic polycarbodiimide and poly(4,4-dicyclohexylmethanecarbodiimide) CECL after melting of granules and films, although overall the most synergetic effect of the CECL is shown by 1,3-phenylenebisoxazoline.
Turbulent compressible flows are traditionally simulated using explicit time integrators applied to discretized versions of the Navier-Stokes equations. However, the associated Courant-Friedrichs-Lewy condition severely restricts the maximum time-step size. Exploiting the Lagrangian nature of the Boltzmann equation’s material derivative, we now introduce a feasible three-dimensional semi-Lagrangian lattice Boltzmann method (SLLBM), which circumvents this restriction. While many lattice Boltzmann methods for compressible flows were restricted to two dimensions due to the enormous number of discrete velocities in three dimensions, the SLLBM uses only 45 discrete velocities. Based on compressible Taylor-Green vortex simulations we show that the new method accurately captures shocks or shocklets as well as turbulence in 3D without utilizing additional filtering or stabilizing techniques other than the filtering introduced by the interpolation, even when the time-step sizes are up to two orders of magnitude larger compared to simulations in the literature. Our new method therefore enables researchers to study compressible turbulent flows by a fully explicit scheme, whose range of admissible time-step sizes is dictated by physics rather than spatial discretization.
The promotion of sustainable packaging is part of the European Green Deal and plays a key role in the EU’s social and political strategy. One option is the use of renewable resources and biomass waste as raw materials for polymer production. Lignocellulose biomass from annual and perennial industrial crops and agricultural residues are a major source of polysaccharides, proteins, and lignin and can also be used to obtain plant-based extracts and essential oils. Therefore, these biomasses are considered as potential substitute for fossil-based resources. Here, the status quo of bio-based polymers is discussed and evaluated in terms of properties related to packaging applications such as gas and water vapor permeability as well as mechanical properties. So far, their practical use is still restricted due to lower performance in fundamental packaging functions that directly influence food quality and safety, the length of shelf life, and thus the amount of food waste. Besides bio-based polymers, this review focuses on plant extracts as active packaging agents. Incorporating extracts of herbs, flowers, trees, and their fruits is inevitable to achieve desired material properties that are capable to prolong the food shelf life. Finally, the adoption potential of packaging based on polymers from renewable resources is discussed from a bioeconomy perspective.
Design of a Medium Voltage Generator with DC-Cascade for High Power Wind Energy Conversion Systems
(2021)
This paper shows a new concept to generate medium voltage (MV) in wind power application to avoid an additional transformer. Therefore, the generator must be redesigned with additional constraints and a new topology for the power rectifier system by using multiple low voltage (LV) power rectifiers connected in series and parallel to increase the DC output voltage. The combination of parallel and series connection of rectifiers is further introduced as DC-cascade. With the resulting DC-cascade, medium output voltage is achieved with low voltage rectifiers and without a bulky transformer. This approach to form a DC-cascade reduces the effort required to achieve medium DC voltage with a simple rectifier system. In this context, a suitable DC-cascade control was presented and verified with a laboratory test setup. A gearless synchronous generator, which is highly segmented so that each segment can be connected to its own power rectifier, is investigated. Due to the mixed AC and DC voltage given by the DC-cascade structure, it becomes more demanding to the design of the generator insulation, which influences the copper fill factor and the design of the cooling system. A design strategy for the overall generator design is carried out considering the new boundary conditions.
The genetic basis of brain tumor development is poorly understood. Here, leukocyte DNA of 21 patients from 15 families with ≥ 2 glioma cases each was analyzed by whole-genome or targeted sequencing. As a result, we identified two families with rare germline variants, p.(A592T) or p.(A817V), in the E-cadherin gene CDH1 that co-segregate with the tumor phenotype, consisting primarily of oligodendrogliomas, WHO grade II/III, IDH-mutant, 1p/19q-codeleted (ODs). Rare CDH1 variants, previously shown to predispose to gastric and breast cancer, were significantly overrepresented in these glioma families (13.3%) versus controls (1.7%). In 68 individuals from 28 gastric cancer families with pathogenic CDH1 germline variants, brain tumors, including a pituitary adenoma, were observed in three cases (4.4%), a significantly higher prevalence than in the general population (0.2%). Furthermore, rare CDH1 variants were identified in tumor DNA of 6/99 (6%) ODs. CDH1 expression was detected in undifferentiated and differentiating oligodendroglial cells isolated from rat brain. Functional studies using CRISPR/Cas9-mediated knock-in or stably transfected cell models demonstrated that the identified CDH1 germline variants affect cell membrane expression, cell migration and aggregation. E-cadherin ectodomain containing variant p.(A592T) had an increased intramolecular flexibility in a molecular dynamics simulation model. E-cadherin harboring intracellular variant p.(A817V) showed reduced β-catenin binding resulting in increased cytosolic and nuclear β-catenin levels reverted by treatment with the MAPK interacting serine/threonine kinase 1 inhibitor CGP 57380. Our data provide evidence for a role of deactivating CDH1 variants in the risk and tumorigenesis of neuroepithelial and epithelial brain tumors, particularly ODs, possibly via WNT/β-catenin signaling.
The analysis of used engine oils from industrial engines enables the study of engine wear and oil degradation in order to evaluate the necessity of oil changes. As the matrix composition of an engine oil strongly depends on its intended application, meaningful diagnostic oil analyses bear considerable challenges. Owing to the broad spectrum of available oil matrices, we have evaluated the applicability of using an internal standard and/or preceding sample digestion for elemental analysis of used engine oils via inductively coupled plasma optical emission spectroscopy (ICP OES). Elements originating from both wear particles and additives as well as particle size influence could be clearly recognized by their distinct digestion behaviour. While a precise determination of most wear elements can be achieved in oily matrix, the measurement of additives is performed preferably after sample digestion. Considering a dataset of physicochemical parameters and elemental composition for several hundred used engine oils, we have further investigated the feasibility of predicting the identity and overall condition of an unknown combustion engine using the machine learning system XGBoost. A maximum accuracy of 89.6% in predicting the engine type was achieved, a mean error of less than 10% of the observed timeframe in predicting the oil running time and even less than 4% for the total engine running time, based purely on common oil check data. Furthermore, obstacles and possibilities to improve the performance of the machine learning models were analysed and the factors that enabled the prediction were explored with SHapley Additive exPlanation (SHAP). Our results demonstrate that both the identification of an unknown engine as well as a lifetime assessment can be performed for a first estimation of the actual sample without requiring meticulous documentation.
Off-lattice Boltzmann methods increase the flexibility and applicability of lattice Boltzmann methods by decoupling the discretizations of time, space, and particle velocities. However, the velocity sets that are mostly used in off-lattice Boltzmann simulations were originally tailored to on-lattice Boltzmann methods. In this contribution, we show how the accuracy and efficiency of weakly and fully compressible semi-Lagrangian off-lattice Boltzmann simulations is increased by velocity sets derived from cubature rules, i.e. multivariate quadratures, which have not been produced by the Gauß-product rule. In particular, simulations of 2D shock-vortex interactions indicate that the cubature-derived degree-nine D2Q19 velocity set is capable to replace the Gauß-product rule-derived D2Q25. Likewise, the degree-five velocity sets D3Q13 and D3Q21, as well as a degree-seven D3V27 velocity set were successfully tested for 3D Taylor–Green vortex flows to challenge and surpass the quality of the customary D3Q27 velocity set. In compressible 3D Taylor–Green vortex flows with Mach numbers on-lattice simulations with velocity sets D3Q103 and D3V107 showed only limited stability, while the off-lattice degree-nine D3Q45 velocity set accurately reproduced the kinetic energy provided by literature.
Ghana suffers from frequent power outages, which can be compensated by off-grid energy solutions. Photovoltaic-hybrid systems become more and more important for rural electrification due to their potential to offer a clean and cost-effective energy supply. However, uncertainties related to the prediction of electrical loads and solar irradiance result in inefficient system control and can lead to an unstable electricity supply, which is vital for the high reliability required for applications within the health sector. Model predictive control (MPC) algorithms present a viable option to tackle those uncertainties compared to rule-based methods, but strongly rely on the quality of the forecasts. This study tests and evaluates (a) a seasonal autoregressive integrated moving average (SARIMA) algorithm, (b) an incremental linear regression (ILR) algorithm, (c) a long short-term memory (LSTM) model, and (d) a customized statistical approach for electrical load forecasting on real load data of a Ghanaian health facility, considering initially limited knowledge of load and pattern changes through the implementation of incremental learning. The correlation of the electrical load with exogenous variables was determined to map out possible enhancements within the algorithms. Results show that all algorithms show high accuracies with a median normalized root mean square error (nRMSE) <0.1 and differing robustness towards load-shifting events, gradients, and noise. While the SARIMA algorithm and the linear regression model show extreme error outliers of nRMSE >1, methods via the LSTM model and the customized statistical approaches perform better with a median nRMSE of 0.061 and stable error distribution with a maximum nRMSE of <0.255. The conclusion of this study is a favoring towards the LSTM model and the statistical approach, with regard to MPC applications within photovoltaic-hybrid system solutions in the Ghanaian health sector.
The actomyosin system generates mechanical work with the execution of the power stroke, an ATP-driven, two-step rotational swing of the myosin-neck that occurs post ATP hydrolysis during the transition from weakly to strongly actin-bound myosin states concomitant with Pi release and prior to ADP dissociation. The activating role of actin on product release and force generation is well documented; however, the communication paths associated with weak-to-strong transitions are poorly characterized. With the aid of mutant analyses based on kinetic investigations and simulations, we identified the W-helix as an important hub coupling the structural changes of switch elements during ATP hydrolysis to temporally controlled interactions with actin that are passed to the central transducer and converter. Disturbing the W-helix/transducer pathway increased actin-activated ATP turnover and reduced motor performance as a consequence of prolonged duration of the strongly actin-attached states. Actin-triggered Pi release was accelerated, while ADP release considerably decelerated, both limiting maximum ATPase, thus transforming myosin-2 into a high-duty-ratio motor. This kinetic signature of the mutant allowed us to define the fractional occupancies of intermediate states during the ATPase cycle providing evidence that myosin populates a cleft-closure state of strong actin interaction during the weak-to-strong transition with bound hydrolysis products before accomplishing the power stroke.