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A second-order L-stable exponential time-differencing (ETD) method is developed by combining an ETD scheme with approximating the matrix exponentials by rational functions having real distinct poles (RDP), together with a dimensional splitting integrating factor technique. A variety of non-linear reaction-diffusion equations in two and three dimensions with either Dirichlet, Neumann, or periodic boundary conditions are solved with this scheme and shown to outperform a variety of other second-order implicit-explicit schemes. An additional performance boost is gained through further use of basic parallelization techniques.
To prevent the reduction of muscle mass and loss of strength coming along with the human aging process, regular training with e.g. a leg press is suitable. However, the risk of training-induced injuries requires the continuous monitoring and controlling of the forces applied to the musculoskeletal system as well as the velocity along the motion trajectory and the range of motion. In this paper, an adaptive norm-optimal iterative learning control algorithm to minimize the knee joint loadings during the leg extension training with an industrial robot is proposed. The response of the algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee and compared to the results of a higher-order iterative learning control algorithm, a robust iterative learning control and a recently proposed conventional norm-optimal iterative learning control algorithm. Although significant improvements in performance are made compared to the conventional norm-optimal iterative learning control algorithm with a small learning factor, for the developed approach as well as the robust iterative learning control algorithm small steady state errors occur.
Exercise training effectively mitigates aging-induced health and fitness impairments. Traditional training recommendations for the elderly focus separately on relevant physiological fitness domains, such as balance, flexibility, strength and endurance. Thus, a more holistic and functional training framework is needed. The proposed agility training concept integratively tackles spatial orientation, stop and go, balance and strength. The presented protocol aims at introducing a two-armed, one-year randomized controlled trial, evaluating the effects of this concept on neuromuscular, cardiovascular, cognitive and psychosocial health outcomes in healthy older adults. Eighty-five participants were enrolled in this ongoing trial. Seventy-nine participants completed baseline testing and were block-randomized to the agility training group or the inactive control group. All participants undergo pre- and post-testing with interim assessment after six months. The intervention group currently receives supervised, group-based agility training twice a week over one year, with progressively demanding perceptual, cognitive and physical exercises. Knee extension strength, reactive balance, dual task gait speed and the Agility Challenge for the Elderly (ACE) serve as primary endpoints and neuromuscular, cognitive, cardiovascular, and psychosocial meassures serve as surrogate secondary outcomes. Our protocol promotes a comprehensive exercise training concept for older adults, that might facilitate stakeholders in health and exercise to stimulate relevant health outcomes without relying on excessively time-consuming physical activity recommendations.
Three-dimensional (3D) full-field measurements provide a comprehensive and accurate validation of finite element (FE) models. For the validation, the result of the model and measurements are compared based on two respective point-sets and this requires the point-sets to be registered in one coordinate system. Point-set registration is a non-convex optimization problem that has widely been solved by the ordinary iterative closest point algorithm. However, this approach necessitates a good initialization without which it easily returns a local optimum, i.e. an erroneous registration. The globally optimal iterative closest point (Go-ICP) algorithm has overcome this drawback and forms the basis for the presented open-source tool that can be used for the validation of FE models using 3D full-field measurements. The capability of the tool is demonstrated using an application example from the field of biomechanics. Methodological problems that arise in real-world data and the respective implemented solution approaches are discussed.
In collaborative research projects, both researchers and practitioners work together solving business-critical challenges. These projects often deal with ETL processes, in which humans extract information from non-machine-readable documents by hand. AI-based machine learning models can help to solve this problem.
Since machine learning approaches are not deterministic, their quality of output may decrease over time. This fact leads to an overall quality loss of the application which embeds machine learning models. Hence, the software qualities in development and production may differ.
Machine learning models are black boxes. That makes practitioners skeptical and increases the inhibition threshold for early productive use of research prototypes. Continuous monitoring of software quality in production offers an early response capability on quality loss and encourages the use of machine learning approaches. Furthermore, experts have to ensure that they integrate possible new inputs into the model training as quickly as possible.
In this paper, we introduce an architecture pattern with a reference implementation that extends the concept of Metrics Driven Research Collaboration with an automated software quality monitoring in productive use and a possibility to auto-generate new test data coming from processed documents in production.
Through automated monitoring of the software quality and auto-generated test data, this approach ensures that the software quality meets and keeps requested thresholds in productive use, even during further continuous deployment and changing input data.
Bacterial cellulose (BC) is a promising material for biomedical applications due to its unique properties such as high mechanical strength and biocompatibility. This article describes the microbiological synthesis, modification, and characterization of the obtained BC-nanocomposites originating from symbiotic consortium Medusomyces gisevii. Two BC-modifications have been obtained: BC-Ag and BC-calcium phosphate (BC-Ca3(PO4)2). Structure and physicochemical properties of the BC and its modifications were investigated by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), atomic force microscopy (AFM), and infrared Fourier spectroscopy as well as by measurements of mechanical and water holding/absorbing capacities. Topographic analysis of the surface revealed multicomponent thick fibrils (150–160 nm in diameter and about 15 µm in length) constituted by 50–60 nm nanofibrils weaved into a left-hand helix. Distinctive features of Ca-phosphate-modified BC samples were (a) the presence of 500–700 nm entanglements and (b) inclusions of Ca3(PO4)2 crystals. The samples impregnated with Ag nanoparticles exhibited numerous roundish inclusions, about 110 nm in diameter. The boundaries between the organic and inorganic phases were very distinct in both cases. The Ag-modified samples also showed a prominent waving pattern in the packing of nanofibrils. The obtained BC gel films possessed water-holding capacity of about 62.35 g/g. However, the dried (to a constant mass) BC-films later exhibited a low water absorption capacity (3.82 g/g). It was found that decellularized BC samples had 2.4 times larger Young’s modulus and 2.2 times greater tensile strength as compared to dehydrated native BC films. We presume that this was caused by molecular compaction of the BC structure.
Biocomposite Materials Based on Carbonized Rice Husk in Biomedicine and Environmental Applications
(2020)
This chapter describes the prospects for biomedical and environmental engineering applications of heterogeneous materials based on nanostructured carbonized rice husk. Efforts in engineering enzymology are focused on the following directions: development and optimization of immobilization methods leading to novel biotechnological and biomedical applications; construction of biocomposite materials based on individual enzymes, multi-enzyme complexes and whole cells, targeted on realization of specific industrial processes. Molecular biological and biochemical studies on cell adhesion focus predominantly on identification, isolation and structural analysis of attachment-responsible biological molecules and their genetic determinants. The chapter provides a short overview of applications of the biocomposite materials based of nanostructured carbonized adsorbents. It emphasizes that further studies and better understanding of the interactions between CNS and microbial cells are necessary. The future use of living cells as biocatalysts, especially in the environmental field, needs more systematic investigations of the microbial adsorption phenomenon.
Background
Osteoporosis is associated with the risk of fractures near the hip. Age and comorbidities increase the perioperative risk. Due to the ageing population, fracture of the proximal femur also proves to be a socio-economic problem. Preventive surgical measures have hardly been used so far.
Methods
10 pairs of human femora from fresh cadavers were divided into control and low-volume femoroplasty groups and subjected to a Hayes fall-loading fracture test. The results of the respective localization and classification of the fracture site, the Singh index determined by computed tomography (CT) examination and the parameters in terms of fracture force, work to fracture and stiffness were evaluated statistically and with the finite element method. In addition, a finite element parametric study with different position angles and variants of the tubular geometry of the femoroplasty was performed.
Findings
Compared to the control group, the work to fracture could be increased by 33.2%. The fracture force increased by 19.9%. The used technique and instrumentation proved to be standardized and reproducible with an average poly(methyl methacrylate) volume of 10.5 ml. The parametric study showed the best results for the selected angle and geometry.
Interpretation
The cadaver studies demonstrated the biomechanical efficacy of the low-volume tubular femoroplasty. The numerical calculations confirmed the optimal choice of positioning as well as the inner and outer diameter of the tube in this setting. The standardized minimally invasive technique with the instruments developed for it could be used in further comparative studies to confirm the measured biomechanical results.
Purpose
This study aims to investigate the biomechanics of handcycling during a continuous load trial (CLT) to assess the mechanisms underlying fatigue in upper body exercise.
Methods
Twelve able-bodied triathletes performed a 30-min CLT at a power output corresponding to lactate threshold in a racing recumbent handcycle mounted on a stationary ergometer. During the CLT, ratings of perceived exertion (RPE), tangential crank kinetics, 3D joint kinematics, and muscular activity of ten muscles of the upper extremity and trunk were examined using motion capturing and surface electromyography.
Results
During the CLT, spontaneously chosen cadence and RPE increased, whereas crank torque decreased. Rotational work was higher during the pull phase. Peripheral RPE was higher compared to central RPE. Joint range of motion decreased for elbow-flexion and radial-duction. Integrated EMG (iEMG) increased in the forearm flexors, forearm extensors, and M. deltoideus (Pars spinalis). An earlier onset of activation was found for M. deltoideus (Pars clavicularis), M. pectoralis major, M. rectus abdominis, M. biceps brachii, and the forearm flexors.
Conclusion
Fatigue-related alterations seem to apply analogously in handcycling and cycling. The most distal muscles are responsible for force transmission on the cranks and might thus suffer most from neuromuscular fatigue. The findings indicate that peripheral fatigue (at similar lactate values) is higher in handcycling compared to leg cycling, at least for inexperienced participants. An increase in cadence might delay peripheral fatigue by a reduced vascular occlusion. We assume that the gap between peripheral and central fatigue can be reduced by sport-specific endurance training.
Electrolyte-insulator-semiconductor (EIS) field-effect sensors belong to a new generation of electronic chips for biochemical sensing, enabling a direct electronic readout. The review gives an overview on recent advances and current trends in the research and development of chemical sensors and biosensors based on the capacitive field-effect EIS structure—the simplest field-effect device, which represents a biochemically sensitive capacitor. Fundamental concepts, physicochemical phenomena underlying the transduction mechanism and application of capacitive EIS sensors for the detection of pH, ion concentrations, and enzymatic reactions, as well as the label-free detection of charged molecules (nucleic acids, proteins, and polyelectrolytes) and nanoparticles, are presented and discussed.
The integration of product data from heterogeneous sources and manufacturers into a single catalog is often still a laborious, manual task. Especially small- and medium-sized enterprises face the challenge of timely integrating the data their business relies on to have an up-to-date product catalog, due to format specifications, low quality of data and the requirement of expert knowledge. Additionally, modern approaches to simplify catalog integration demand experience in machine learning, word vectorization, or semantic similarity that such enterprises do not have. Furthermore, most approaches struggle with low-quality data. We propose Attribute Label Ranking (ALR), an easy to understand and simple to adapt learning approach. ALR leverages a model trained on real-world integration data to identify the best possible schema mapping of previously unknown, proprietary, tabular format into a standardized catalog schema. Our approach predicts multiple labels for every attribute of an inpu t column. The whole column is taken into consideration to rank among these labels. We evaluate ALR regarding the correctness of predictions and compare the results on real-world data to state-of-the-art approaches. Additionally, we report findings during experiments and limitations of our approach.
The steel industry in the European Union (EU), important for the economy as a whole, faces various challenges. These are inter alia volatile prices for relevant input factors, uncertainties concerning the regulation of CO₂-emissions and market shocks caused by the recently introduced additional import duties in the US, which is an important sales market. We examine primary and secondary effects of these challenges on the steel industry in the EU and their impacts on European and global level. Developing and using a suitable meta-model, we analyze the competitiveness of key steel producing countries with respect to floor prices depending on selected cost factors and draw conclusions on the impacts in the trade of steel on emissions, energy demand, on the involvement of developing countries in the value chain as well on the need for innovations to avoid relocations of production. Hence, our study contributes to the assessment of sustainable industrial development, which is aimed by the Sustainability Development Goal “Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation countries”. By applying information on country-specific Human Development Indexes (reflecting aspects of life expectancy, education, and per capita income), we show that relocating energy-intensive industries from the EU may not only increase global energy demand and CO₂-emissions, but may also be to the disadvantage of developing countries.
Combining physiological relevance and throughput for in vitro cardiac contractility measurement
(2020)
Despite increasing acceptance of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) in safety pharmacology, controversy remains about the physiological relevance of existing in vitro models for their mechanical testing. We hypothesize that existing signs of immaturity of the cell models result from an improper mechanical environment. We cultured hiPSC-CMs in a 96-well format on hyperelastic silicone membranes imitating their native mechanical environment, resulting in physiological responses to compound stimuli.We validated cell responses on the FLEXcyte 96, with a set of reference compounds covering a broad range of cellular targets, including ion channel modulators, adrenergic receptor modulators and kinase inhibitors. Acute (10 - 30 min) and chronic (up to 7 days) effects were investigated. Furthermore, the measurements were complemented with electromechanical models based on electrophysiological recordings of the used cell types.hiPSC-CMs were cultured on freely-swinging, ultra-thin and hyperelastic silicone membranes. The weight of the cell culture medium deflects the membranes downwards. Rhythmic contraction of the hiPSC-CMs resulted in dynamic deflection changes which were quantified by capacitive distance sensing. The cells were cultured for 7 days prior to compound addition. Acute measurements were conducted 10-30 minutes after compound addition in standard culture medium. For chronic treatment, compound-containing medium was replaced daily for up to 7 days. Electrophysiological properties of the employed cell types were recorded by automated patch-clamp (Patchliner) and the results were integrated into the electromechanical model of the system.Calcium channel agonist S Bay K8644 and beta-adrenergic stimulator isoproterenol induced significant positive inotropic responses without additional external stimulation. Kinase inhibitors displayed cardiotoxic effects on a functional level at low concentrations. The system-integrated analysis detected alterations in beating shape as well as frequency and arrhythmic events and we provide a quantitative measure of these.
With the variety of toothbrushes on the market, the question arises, which toothbrush is best suited to maintain oral health? This thematic review focuses first on plaque formation mechanisms and then on the plaque removal effectiveness of ultrasonic toothbrushes and their potential in preventing oral diseases like periodontitis, gingivitis, and caries. We overviewed the physical effects that occurred during brushing and tried to address the question of whether ultrasonic toothbrushes effectively reduced the microbial burden by increasing the hydrodynamic forces. The results of published studies show that electric toothbrushes, which combine ultrasonic and sonic (or acoustic and mechanic) actions, may have the most promising effect on good oral health. Existing ultrasonic/sonic toothbrush models do not significantly differ regarding the removal of dental biofilm and the reduction of gingival inflammation compared with other electrically powered toothbrushes, whereas the manual toothbrushes show a lower effectiveness.
Design, evaluation and comparison of endorectal coils for hybrid MR-PET imaging of the prostate
(2020)
Prostate cancer is one of the most common cancers among men and its early detection is critical for its successful treatment. The use of multimodal imaging, such as MR-PET, is most advantageous as it is able to provide detailed information about the prostate. However, as the human prostate is flexible and can move into different positions under external conditions, it is important to localise the focused region-of-interest using both MRI and PET under identical circumstances. In this work, we designed five commonly used linear and quadrature radiofrequency surface coils suitable for hybrid MR-PET use in endorectal applications. Due to the endorectal design and the shielded PET insert, the outer face of the coils investigated was curved and the region to be imaged was outside the volume of the coil. The tilting angles of the coils were varied with respect to the main magnetic field direction. This was done to approximate the various positions from which the prostate could be imaged. The transmit efficiencies and safety excitation efficiencies from simulations, together with the signal-to-noise ratios from the MR images were calculated and analysed. Overall, it was found that the overlapped loops driven in quadrature were superior to the other types of coils we tested. In order to determine the effect of the different coil designs on PET, transmission scans were carried out, and it was observed that the differences between attenuation maps with and without the coils were negligible. The findings of this work can provide useful guidance for the integration of such coil designs into MR-PET hybrid systems in the future.
Within the present work a sterilization process by a heated gas mixture that contains hydrogen peroxide (H₂O₂) is validated by experiments and numerical modeling techniques. The operational parameters that affect the sterilization efficacy are described alongside the two modes of sterilization: gaseous and condensed H₂O₂. Measurements with a previously developed H₂O₂ gas sensor are carried out to validate the applied H₂O₂ gas concentration during sterilization. We performed microbiological tests at different H₂O₂ gas concentrations by applying an end-point method to carrier strips, which contain different inoculation loads of Geobacillus stearothermophilus spores. The analysis of the sterilization process of a pharmaceutical glass vial is performed by numerical modeling. The numerical model combines heat- and advection-diffusion mass transfer with vapor–pressure equations to predict the location of condensate formation and the concentration of H₂O₂ at the packaging surfaces by changing the gas temperature. For a sterilization process of 0.7 s, a H₂O₂ gas concentration above 4% v/v is required to reach a log-count reduction above six. The numerical results showed the location of H₂O₂ condensate formation, which decreases with increasing sterilant-gas temperature. The model can be transferred to different gas nozzle- and packaging geometries to assure the absence of H₂O₂ residues.
Extracellular acidification is a basic indicator for alterations in two vital metabolic pathways: glycolysis and cellular respiration. Measuring these alterations by monitoring extracellular acidification using cell-based biosensors such as LAPS plays an important role in studying these pathways whose disorders are associated with numerous diseases including cancer. However, the surface of the biosensors must be specially tailored to ensure high cell compatibility so that cells can represent more in vivo-like behavior, which is critical to gain more realistic in vitro results from the analyses, e.g., drug discovery experiments. In this work, O2 plasma patterning on the LAPS surface is studied to enhance surface features of the sensor chip, e.g., wettability and biofunctionality. The surface treated with O2 plasma for 30 s exhibits enhanced cytocompatibility for adherent CHO–K1 cells, which promotes cell spreading and proliferation. The plasma-modified LAPS chip is then integrated into a microfluidic system, which provides two identical channels to facilitate differential measurements of the extracellular acidification of CHO–K1 cells. To the best of our knowledge, it is the first time that extracellular acidification within microfluidic channels is quantitatively visualized as differential (bio-)chemical images.
We propose the so-called chance constrained programming model of stochastic programming theory to analyze limit and shakedown loads of structures under random strength with a lognormal distribution. A dual chance constrained programming algorithm is developed to calculate simultaneously both the upper and lower bounds of the plastic collapse limit and the shakedown limit. The edge-based smoothed finite element method (ES-FEM) is used with three-node linear triangular elements.