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Humic substances possess distinctive chemical features enabling their use in many advanced applications, including biomedical fields. No chemicals in nature have the same combination of specific chemical and biological properties as humic substances. Traditional medicine and modern research have demonstrated that humic substances from different sources possess immunomodulatory and anti-inflammatory properties, which makes them suitable for the prevention and treatment of chronic dermatoses, allergic rhinitis, atopic dermatitis, and other conditions characterized by inflammatory and allergic responses [1-4]. The use of humic compounds as agentswith antifungal and antiviral properties shows great potential [5-7].
Pulmonary arterial cannulation is a common and effective method for percutaneous mechanical circulatory support for concurrent right heart and respiratory failure [1]. However, limited data exists to what effect the positioning of the cannula has on the oxygen perfusion throughout the pulmonary artery (PA). This study aims to evaluate, using computational fluid dynamics (CFD), the effect of different cannula positions in the PA with respect to the oxygenation of the different branching vessels in order for an optimal cannula position to be determined. The four chosen different positions (see Fig. 1) of the cannulas are, in the lower part of the main pulmonary artery (MPA), in the MPA at the junction between the right pulmonary artery (RPA) and the left pulmonary artery (LPA), in the RPA at the first branch of the RPA and in the LPA at the first branch of the LPA.
Magnetic nanoparticles (MNP) are investigated with great interest for biomedical applications in diagnostics (e.g. imaging: magnetic particle imaging (MPI)), therapeutics (e.g. hyperthermia: magnetic fluid hyperthermia (MFH)) and multi-purpose biosensing (e.g. magnetic immunoassays (MIA)). What all of these applications have in common is that they are based on the unique magnetic relaxation mechanisms of MNP in an alternating magnetic field (AMF). While MFH and MPI are currently the most prominent examples of biomedical applications, here we present results on the relatively new biosensing application of frequency mixing magnetic detection (FMMD) from a simulation perspective. In general, we ask how the key parameters of MNP (core size and magnetic anisotropy) affect the FMMD signal: by varying the core size, we investigate the effect of the magnetic volume per MNP; and by changing the effective magnetic anisotropy, we study the MNPs’ flexibility to leave its preferred magnetization direction. From this, we predict the most effective combination of MNP core size and magnetic anisotropy for maximum signal generation.
Aircraft configurations with propellers have been drawing more attention in recent times, partly due to new propulsion concepts based on hydrogen fuel cells and electric motors. These configurations are prone to whirl flutter, which is an aeroelastic instability affecting airframes with elastically supported propellers. It commonly needs to be mitigated already during the design phase of such configurations, requiring, among other things, unsteady aerodynamic transfer functions for the propeller. However, no comprehensive assessment of unsteady propeller aerodynamics for aeroelastic analysis is available in the literature. This paper provides a detailed comparison of nine different low- to mid-fidelity aerodynamic methods, demonstrating their impact on linear, unsteady aerodynamics, as well as whirl flutter stability prediction. Quasi-steady and unsteady methods for blade lift with or without coupling to blade element momentum theory are evaluated and compared to mid-fidelity potential flow solvers (UPM and DUST) and classical, derivative-based methods. Time-domain identification of frequency-domain transfer functions for the unsteady propeller hub loads is used to compare the different methods. Predictions of the minimum required pylon stiffness for stability show good agreement among the mid-fidelity methods. The differences in the stability predictions for the low-fidelity methods are higher. Most methods studied yield a more unstable system than classical, derivative-based whirl flutter analysis, indicating that the use of more sophisticated aerodynamic modeling techniques might be required for accurate whirl flutter prediction.
Landslides, rock falls or related subaerial and subaqueous mass slides can generate devastating impulse waves in adjacent waterbodies. Such waves can occur in lakes and fjords, or due to glacier calving in bays or at steep ocean coastlines. Infrastructure and residential houses along coastlines of those waterbodies are often situated on low elevation terrain, and are potentially at risk from inundation. Impulse waves, running up a uniform slope and generating an overland flow over an initially dry adjacent horizontal plane, represent a frequently found scenario, which needs to be better understood for disaster planning and mitigation. This study presents a novel set of large-scale flume test focusing on solitary waves propagating over a 1:14.5 slope and breaking onto a horizontal section. Examining the characteristics of overland flow, this study gives, for the first time, insight into the fundamental process of overland flow of a broken solitary wave: its shape and celerity, as well as its momentum when wave breaking has taken place beforehand.
Motile cilia are hair-like cell extensions present in multiple organs of the body. How cilia coordinate their regular beat in multiciliated epithelia to move fluids remains insufficiently understood, particularly due to lack of rigorous quantification. We combine here experiments, novel analysis tools, and theory to address this knowledge gap. We investigate collective dynamics of cilia in the zebrafish nose, due to its conserved properties with other ciliated tissues and its superior accessibility for non-invasive imaging. We revealed that cilia are synchronized only locally and that the size of local synchronization domains increases with the viscosity of the surrounding medium. Despite the fact that synchronization is local only, we observed global patterns of traveling metachronal waves across the multiciliated epithelium. Intriguingly, these global wave direction patterns are conserved across individual fish, but different for left and right nose, unveiling a chiral asymmetry of metachronal coordination. To understand the implications of synchronization for fluid pumping, we used a computational model of a regular array of cilia. We found that local metachronal synchronization prevents steric collisions and improves fluid pumping in dense cilia carpets, but hardly affects the direction of fluid flow. In conclusion, we show that local synchronization together with tissue-scale cilia alignment are sufficient to generate metachronal wave patterns in multiciliated epithelia, which enhance their physiological function of fluid pumping.
During rapid deceleration of the body, tendons buffer part of the elongation of the muscle-tendon unit (MTU), enabling safe energy dissipation via eccentric muscle contraction. Yet, the influence of changes in tendon stiffness within the physiological range upon these lengthening contractions is unknown. This study aimed to examine the effect of training-induced stiffening of the Achilles tendon on triceps surae muscle-tendon behavior during a landing task. Twenty-one male subjects were assigned to either a 10-week resistance-training program consisting of single-leg isometric plantarflexion (n = 11) or to a non-training control group (n = 10). Before and after the training period, plantarflexion force, peak Achilles tendon strain and stiffness were measured during isometric contractions, using a combination of dynamometry, ultrasound and kinematics data. Additionally, testing included a step-landing task, during which joint mechanics and lengths of gastrocnemius and soleus fascicles, Achilles tendon, and MTU were determined using synchronized ultrasound, kinematics and kinetics data collection. After training, plantarflexion strength and Achilles tendon stiffness increased (15 and 18%, respectively), and tendon strain during landing remained similar. Likewise, lengthening and negative work produced by the gastrocnemius MTU did not change detectably. However, in the training group, gastrocnemius fascicle length was offset (8%) to a longer length at touch down and, surprisingly, fascicle lengthening and velocity were reduced by 27 and 21%, respectively. These changes were not observed for soleus fascicles when accounting for variation in task execution between tests. These results indicate that a training-induced increase in tendon stiffness does not noticeably affect the buffering action of the tendon when the MTU is rapidly stretched. Reductions in gastrocnemius fascicle lengthening and lengthening velocity during landing occurred independently from tendon strain. Future studies are required to provide insight into the mechanisms underpinning these observations and their influence on energy dissipation.
This study describes the development of a new combined polysaccharide-matrix-based technology for the immobilization of Lactobacillus rhamnosus GG (LGG) bacteria in biofilm form. The new composition allows for delivering the bacteria to the digestive tract in a manner that improves their robustness compared with planktonic cells and released biofilm cells. Granules consisting of a polysaccharide matrix with probiotic biofilms (PMPB) with high cell density (>9 log CFU/g) were obtained by immobilization in the optimized nutrient medium. Successful probiotic loading was confirmed by fluorescence microscopy and scanning electron microscopy. The developed prebiotic polysaccharide matrix significantly enhanced LGG viability under acidic (pH 2.0) and bile salt (0.3%) stress conditions. Enzymatic extract of feces, mimicking colon fluid in terms of cellulase activity, was used to evaluate the intestinal release of probiotics. PMPB granules showed the ability to gradually release a large number of viable LGG cells in the model colon fluid. In vivo, the oral administration of PMPB granules in rats resulted in the successful release of probiotics in the colon environment. The biofilm-forming incubation method of immobilization on a complex polysaccharide matrix tested in this study has shown high efficacy and promising potential for the development of innovative biotechnologies.
Comparison of different training algorithms for the leg extension training with an industrial robot
(2018)
In the past, different training scenarios have been developed and implemented on robotic research platforms, but no systematic analysis and comparison have been done so far. This paper deals with the comparison of an isokinematic (motion with constant velocity) and an isotonic (motion against constant weight) training algorithm. Both algorithms are designed for a robotic research platform consisting of a 3D force plate and a high payload industrial robot, which allows leg extension training with arbitrary six-dimensional motion trajectories. In the isokinematic as well as the isotonic training algorithm, individual paths are defined i n C artesian s pace by sufficient s upport p oses. I n t he i sotonic t raining s cenario, the trajectory is adapted to the measured force as the robot should only move along the trajectory as long as the force applied by the user exceeds a minimum threshold. In the isotonic training scenario however, the robot’s acceleration is a function of the force applied by the user. To validate these findings, a simulative experiment with a simple linear trajectory is performed. For this purpose, the same force path is applied in both training scenarios. The results illustrate that the algorithms differ in the force dependent trajectory adaption.
Training-induced increase in Achilles tendon stiffness affects tendon strain pattern during running
(2019)
Background
During the stance phase of running, the elasticity of the Achilles tendon enables the utilisation of elastic energy and allows beneficial contractile conditions for the triceps surae muscles. However, the effect of changes in tendon mechanical properties induced by chronic loading is still poorly understood. We tested the hypothesis that a training-induced increase in Achilles tendon stiffness would result in reduced tendon strain during the stance phase of running, which would reduce fascicle strains in the triceps surae muscles, particularly in the mono-articular soleus.
Methods
Eleven subjects were assigned to a training group performing isometric singleleg plantarflexion contractions three times per week for ten weeks, and another ten subjects formed a control group. Before and after the training period, Achilles tendon stiffness was estimated, and muscle-tendon mechanics were assessed during running at preferred speed using ultrasonography, kinematics and kinetics.
Results
Achilles tendon stiffness increased by 18% (P <0:01) in the training group, but the associated reduction in strain seen during isometric contractions was not statistically significant. Tendon elongation during the stance phase of running was similar after training, but tendon recoil was reduced by 30% (P <0:01), while estimated tendon force remained unchanged. Neither gastrocnemius medialis nor soleus fascicle shortening during stance was affected by training.
Discussion
These results show that a training-induced increase in Achilles tendon
stiffness altered tendon behaviour during running. Despite training-induced changes in tendon mechanical properties and recoil behaviour, the data suggest that fascicle shortening patterns were preserved for the running speed that we examined. The asymmetrical changes in tendon strain patterns supports the notion that simple inseries models do not fully explain the mechanical output of the muscle-tendon unit during a complex task like running.
The MYOTONES experiment is the first to monitor changes in the basic biomechanical properties (tone, elasticity and stiffness) of the resting human myofascial system due to microgravity with a oninvasive, portable device on board the ISS. The MyotonPRO device applies several brief mechanical stimuli to the surface of the skin, and the natural oscillation signals of the tissue beneath are detected and computed by the MyotonPRO. Thus, an objective, quick and easy determination of the state of the underlying tissue is possible.
Two preflight, four inflight and four post flight measurements were performed on a male astronaut using the same 10 measurement points (MP) for each session. MPs were located on the plantar fascia, Achilles tendon, M. soleus, M. gastrocnemius, M. multifidus, M. splenius capitis, M. deltoideus anterior, M. rectus femoris, infrapatellar tendon, M. tibialis anterior. Subcutaneous tissues thickness above the MPs was measured using ultrasound imaging. Magnetic resonance images (MRI) of lower limb muscles and functional tests were also performed pre- and postflight.
Our first measurements on board the ISS confirmed increased tone and stiffness of the lumbar multifidus muscle, an important trunk stabilizer, dysfunction of which is known to be associated with back pain. Furthermore, reduced tone and stiffness of Achilles tendon and plantar fascia were observed inflight vs. preflight, confirming previous findings from terrestrial analog studies and parabolic
flights. Unexpectedly, the deltoid showed negative inflight changes in tone and stiffness, and increased elasticity, suggesting a potential risk of muscle atrophy in longer spaceflight that should be addressed by adequate inflight countermeasure protocols. Most values from limb and back MPS showed deflected patterns (in either directions) from inflight shortly after the re-entry phase on the landing day and one week later. Most parameter values then normalized to baseline after 3 weeks likely due to 1G re-adaptation and possible outcome of the reconditioning protocol. No major changes in subcutaneous tissues thickness above the MPs were found inflight vs preflight, suggesting no bias (i.e., fluid shift, extreme tissue thickening or loss). Pre- and postflight MRI and functional tests showed negligible changes in calf muscle size, power and force, which is likely due to training effects from current inflight exercise protocols.
The MYOTONES experiment is currently ongoing to collect data from further crew members. The potential impact of this research is to better understand the effects of microgravity and countermeasures over the time course of an ISS mission cycle. This will enable exercise countermeasures to be tailored
By developing innovative solutions to social and environmental problems, sustainable ventures carry greatpotential. Entrepreneurship which focuses especially on new venture creation can be developed through education anduniversities, in particular, are called upon to provide an impetus for social change. But social innovations are associatedwith certain hurdles, which are related to the multi-dimensionality, i.e. the tension between creating social,environmental and economic value and dealing with a multiplicity of stakeholders. The already complex field ofentrepreneurship education has to face these challenges. This paper, therefore, aims to identify starting points for theintegration of sustainability into entrepreneurship education. To pursue this goal experiences from three differentproject initiatives between the partner universities: Lapland University of Applied Sciences, FH Aachen University ofApplied Sciences and Turiba University are reflected and findings are systematically condensed into recommendationsfor education on sustainable entrepreneurship.
Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.
Neuromuscular strength training of the leg extensor muscles plays an important role in the rehabilitation and prevention of age and wealth related diseases. In this paper, we focus on the design and implementation of a Cartesian admittance control scheme for isotonic training, i.e. leg extension and flexion against a predefined weight. For preliminary testing and validation of the designed algorithm an experimental research and development platform consisting of an
industrial robot and a force plate mounted at its end-effector has been used. Linear, diagonal and arbitrary two-dimensional motion trajectories with different weights for the leg extension and flexion part are applied. The proposed algorithm is easily adaptable to trajectories consisting of arbitrary six-dimensional poses and allows the implementation of individualized trajectories.
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.
Achilles tendon rupture (ATR) patients have persistent functional deficits in the triceps surae muscle–tendon unit (MTU). The complex remodeling of the MTU accompanying these deficits remains poorly understood. The purpose of the present study was to associate in vivo and in silico data to investigate the relations between changes inMTU properties and strength deficits inATR patients. Methods: Elevenmale subjects who had undergone surgical repair of complete unilateral ATR were examined 4.6 ± 2.0 (mean ± SD) yr after rupture. Gastrocnemius medialis (GM) tendon stiffness, morphology, and muscle architecture were determined using ultrasonography. The force–length relation of the plantar flexor muscles was assessed at five ankle joint angles. In addition, simulations (OpenSim) of the GM MTU force–length properties were performed with various iterations of MTU properties found between the unaffected and the affected side. Results: The affected side of the patients displayed a longer, larger, and stiffer GM tendon (13% ± 10%, 105% ± 28%, and 54% ± 24%, respectively) compared with the unaffected side. The GM muscle fascicles of the affected side were shorter (32% ± 12%) and with greater pennation angles (31% ± 26%). A mean deficit in plantarflexion moment of 31% ± 10% was measured. Simulations indicate that pairing an intact muscle with a longer tendon shifts the optimal angular range of peak force outside physiological angular ranges, whereas the shorter muscle fascicles and tendon stiffening seen in the affected side decrease this shift, albeit incompletely. Conclusions: These results suggest that the substantial changes in MTU properties found in ATR patients may partly result from compensatory remodeling, although this process appears insufficient to fully restore muscle function.
Performing tasks, such as running and jumping, requires activation of the agonist and antagonist muscles before (motor unit pre-activation) and during movement performance (Santello and Mcdonagh, 1998). A well-timed and regulated muscle activation elicits a stretch-shortening cycle (SSC) response, naturally occurring in bouncing movements (Ishikawa and Komi, 2004; Taube et al., 2012). By definition, the SSC describes the stretching of a pre-activated muscle-tendon complex immediately followed by a muscle shortening in the concentric push-off phase (Komi, 1984).
Given the importance of SSC actions for human movement, it is not surprising that many studies investigated the biomechanics of this phenomenon; in particular, drop jumps (DJs) represent a good paradigm to study muscle fascicle and tendon behavior in ballistic movements involving the SSC.
Within a DJ, three main phases [pre-activation, braking, and push-off (PO; Komi, 2000)] have been recognized and extensively studied in common and challenging conditions, such as changes in load, falling height, or simulated hypo-gravity (Avela et al., 1994; Arampatzis et al., 2001; Fukashiro et al., 2005; Ishikawa et al., 2005; Sousa et al., 2007; Ritzmann et al., 2016; Helm et al., 2020).
These studies show that the timing and amount of triceps-surae muscle-tendon unit pre-activation in DJs are differentially regulated based on the load applied to the muscle, being optimal in normal “Earth” gravity conditions (Avela et al., 1994), but decreased in simulated hypo-gravity, hyper-gravity (Avela et al., 1994; Ritzmann et al., 2016), or unknown conditions (i.e., unknown falling heights; Helm et al., 2020). Some authors indicated that, when falling from heights different from the optimal one [defined as the drop height giving a maximum DJ performance indicated as peak ground reaction force (GRF) or jump high], electromyographic (EMG) activity of the plantar flexors increases from lower than optimal to higher than optimal heights (Ishikawa and Komi, 2004; Sousa et al., 2007).
These findings highlight the ability of the central nervous system to regulate the timing and amount of pre-activation according to different jumping conditions, thus regulating muscle fascicle length, tendon and joint stiffness as well as position, in order to safely land on the ground and quickly re-bounce.
Similarly, to pre-activation, also in the braking phase, the plantar flexors are differentially regulated. In optimal height (i.e., load) jumping conditions, gastrocnemius medialis (GM) fascicles shorten at early ground contact (possibly due to the intervention of the stretch reflex; Gollhofer et al., 1992) and behave quasi-isometrically in the late braking phase, enabling tendon elongation, and storage of elastic energy (Gollhofer et al., 1992; Fukashiro et al., 2005; Sousa et al., 2007). When increasing the falling height (augmenting the impact GRF), the quasi-isometric behavior of fascicles disappears, and fast fascicle lengthening occurs (Ishikawa et al., 2005; Sousa et al., 2007).
In the third and last PO phase, fascicles shorten and the tendon releases the elastic energy previously stored. Bobbert et al. (1987) reported no influence of jumping height on the work done and on the net vertical impulse assessed during PO; this observation suggests that, despite an optimal DJ performance might be achieved only in specific conditions (falling heights, loads), the central nervous system seems to be able to regulate muscle behavior in order to effectively perform the required task also in challenging situations.
Although the regulation of triceps-surae muscle-tendon unit in DJs has been extensively investigated, very few studies focused on sarcomeres behavior during the performance of this SSC movement (Kurokawa et al., 2003; Fukashiro et al., 2005, 2006). Sarcomeres represent muscle contractile units and are known to express different amounts of force depending on their length (Gordon et al., 1966; Walker and Schrodt, 1974); thus, understanding the time course of their responses during DJs is fundamental to gain further insights into muscle force-generating capacity. In vivo measurement of sarcomere length in humans has been so far been performed only in static positions and under highly controlled experimental conditions (Llewellyn et al., 2008; Sanchez et al., 2015). Instead, human sarcomere length estimation (achieved by dividing GM measured fascicle length for a fixed sarcomere number) in dynamic contractions provided an indirect measure of sarcomere operating range during squat jump, countermovement jump, and DJ (Fukashiro et al., 2005, 2006; Kurokawa et al., 2003). The results of these studies showed that sarcomeres operate in the ascending limb of their length-tension (L-T) relationship in all types of jumps, and particularly so in DJ.
However, most of the available observations on sarcomere and muscle fascicle behavior were made in condition of constant gravity. Thus, in order to understand how sarcomere and muscle fascicle length are regulated in variable gravity conditions, we performed experiments in a parabolic flight, involving variable gravity levels, ranging from about zero-g to about double the Earth’s gravity (1 g; Waldvogel et al., 2021).
Specifically, the aims of the present study were as follows:
1. To investigate the ability of the neuromuscular system in regulating fascicle length in response to conditions of variable gravity.
2. To estimate sarcomere operative length in the different DJ phases, in order to calculate its theoretical force production and its possible modulation in conditions of variable gravity.
We hypothesized that muscle fascicles would be differentially regulated in different gravity conditions compared to 1 g, particularly in anticipation of landing and re-bouncing in unknown gravity levels. In addition, we hypothesized that sarcomeres would operate in the upper part of the ascending limb of their L-T relationship, possibly lengthening during the braking phase (especially in hyper-gravity) while operating quasi-isometrically in 1 g.
The compliant nature of distal limb muscle-tendon units is traditionally considered suboptimal in explosive movements when positive joint work is required. However, during accelerative running, ankle joint net mechanical work is positive. Therefore, this study aims to investigate how plantar flexor muscle-tendon behavior is modulated during fast accelerations. Eleven female sprinters performed maximum sprint accelerations from starting blocks, while gastrocnemius muscle fascicle lengths were estimated using ultrasonography. We combined motion analysis and ground reaction force measurements to assess lower limb joint kinematics and kinetics, and to estimate gastrocnemius muscle-tendon unit length during the first two acceleration steps. Outcome variables were resampled to the stance phase and averaged across three to five trials. Relevant scalars were extracted and analyzed using one-sample and two-sample t-tests, and vector trajectories were compared using statistical parametric mapping. We found that an uncoupling of muscle fascicle behavior from muscle-tendon unit behavior is effectively used to produce net positive mechanical work at the joint during maximum sprint acceleration. Muscle fascicles shortened throughout the first and second steps, while shortening occurred earlier during the first step, where negative joint work was lower compared with the second step. Elastic strain energy may be stored during dorsiflexion after touchdown since fascicles did not lengthen at the same time to dissipate energy. Thus, net positive work generation is accommodated by the reuse of elastic strain energy along with positive gastrocnemius fascicle work. Our results show a mechanism of how muscles with high in-series compliance can contribute to net positive joint work.
This study aims to quantify the kinematics, kinetics and muscular activity of all-out handcycling exercise and examine their alterations during the course of a 15-s sprint test. Twelve able-bodied competitive triathletes performed a 15-s all-out sprint test in a recumbent racing handcycle that was attached to an ergometer. During the sprint test, tangential crank kinetics, 3D joint kinematics and muscular activity of 10 muscles of the upper extremity and trunk were examined using a power metre, motion capturing and surface electromyography (sEMG), respectively. Parameters were compared between revolution one (R1), revolution two (R2), the average of revolution 3 to 13 (R3) and the average of the remaining revolutions (R4). Shoulder abduction and internal-rotation increased, whereas maximal shoulder retroversion decreased during the sprint. Except for the wrist angles, angular velocity increased for every joint of the upper extremity. Several muscles demonstrated an increase in muscular activation, an earlier onset of muscular activation in crank cycle and an increased range of activation. During the course of a 15-s all-out sprint test in handcycling, the shoulder muscles and the muscles associated to the push phase demonstrate indications for short-duration fatigue. These findings are helpful to prevent injuries and improve performance in all-out handcycling.
Rehabilitative body weight supported gait training aims at restoring walking function as a key element in activities of daily living. Studies demonstrated reductions in muscle and joint forces, while kinematic gait patterns appear to be preserved with up to 30% weight support. However, the influence of body weight support on muscle architecture, with respect to fascicle and series elastic element behavior is unknown, despite this having potential clinical implications for gait retraining. Eight males (31.9 ± 4.7 years) walked at 75% of the speed at which they typically transition to running, with 0% and 30% body weight support on a lower-body positive pressure treadmill. Gastrocnemius medialis fascicle lengths and pennation angles were measured via ultrasonography. Additionally, joint kinematics were analyzed to determine gastrocnemius medialis muscle–tendon unit lengths, consisting of the muscle's contractile and series elastic elements. Series elastic element length was assessed using a muscle–tendon unit model. Depending on whether data were normally distributed, a paired t-test or Wilcoxon signed rank test was performed to determine if body weight supported walking had any effects on joint kinematics and fascicle–series elastic element behavior. Walking with 30% body weight support had no statistically significant effect on joint kinematics and peak series elastic element length. Furthermore, at the time when peak series elastic element length was achieved, and on average across the entire stance phase, muscle–tendon unit length, fascicle length, pennation angle, and fascicle velocity were unchanged with respect to body weight support. In accordance with unchanged gait kinematics, preservation of fascicle–series elastic element behavior was observed during walking with 30% body weight support, which suggests transferability of gait patterns to subsequent unsupported walking.
Altered gastrocnemius contractile behavior in former achilles tendon rupture patients during walking
(2022)
Achilles tendon rupture (ATR) remains associated with functional limitations years after injury. Architectural remodeling of the gastrocnemius medialis (GM) muscle is typically observed in the affected leg and may compensate force deficits caused by a longer tendon. Yet patients seem to retain functional limitations during—low-force—walking gait. To explore the potential limits imposed by the remodeled GM muscle-tendon unit (MTU) on walking gait, we examined the contractile behavior of muscle fascicles during the stance phase. In a cross-sectional design, we studied nine former patients (males; age: 45 ± 9 years; height: 180 ± 7 cm; weight: 83 ± 6 kg) with a history of complete unilateral ATR, approximately 4 years post-surgery. Using ultrasonography, GM tendon morphology, muscle architecture at rest, and fascicular behavior were assessed during walking at 1.5 m⋅s–1 on a treadmill. Walking patterns were recorded with a motion capture system. The unaffected leg served as control. Lower limbs kinematics were largely similar between legs during walking. Typical features of ATR-related MTU remodeling were observed during the stance sub-phases corresponding to series elastic element (SEE) lengthening (energy storage) and SEE shortening (energy release), with shorter GM fascicles (36 and 36%, respectively) and greater pennation angles (8° and 12°, respectively). However, relative to the optimal fascicle length for force production, fascicles operated at comparable length in both legs. Similarly, when expressed relative to optimal fascicle length, fascicle contraction velocity was not different between sides, except at the time-point of peak series elastic element (SEE) length, where it was 39 ± 49% lower in the affected leg. Concomitantly, fascicles rotation during contraction was greater in the affected leg during the whole stance-phase, and architectural gear ratios (AGR) was larger during SEE lengthening. Under the present testing conditions, former ATR patients had recovered a relatively symmetrical walking gait pattern. Differences in seen AGR seem to accommodate the profound changes in MTU architecture, limiting the required fascicle shortening velocity. Overall, the contractile behavior of the GM fascicles does not restrict length- or velocity-dependent force potentials during this locomotor task.
Market abstraction of energy markets and policies - application in an agent-based modeling toolbox
(2023)
In light of emerging challenges in energy systems, markets are prone to changing dynamics and market design. Simulation models are commonly used to understand the changing dynamics of future electricity markets. However, existing market models were often created with specific use cases in mind, which limits their flexibility and usability. This can impose challenges for using a single model to compare different market designs. This paper introduces a new method of defining market designs for energy market simulations. The proposed concept makes it easy to incorporate different market designs into electricity market models by using relevant parameters derived from analyzing existing simulation tools, morphological categorization and ontologies. These parameters are then used to derive a market abstraction and integrate it into an agent-based simulation framework, allowing for a unified analysis of diverse market designs. Furthermore, we showcase the usability of integrating new types of long-term contracts and over-the-counter trading. To validate this approach, two case studies are demonstrated: a pay-as-clear market and a pay-as-bid long-term market. These examples demonstrate the capabilities of the proposed framework.
Antibias training is increasingly demanded and practiced in academia and industry to increase employees’ sensitivity to discrimination, racism, and diversity. Under the heading of “Diversity Management,” antibias trainings are mainly offered as one-off workshops intending to raise awareness of unconscious biases, create a diversity-affirming corporate culture, promote awareness of the potential of
diversity, and ultimately enable the reflection of diversity in development processes. However, coming from childhood education, research and scientific articles on the sustainable effectiveness of antibias in adulthood, especially in academia, are very scarce. In order to fill this research gap, the article aims to explore how sustainable the effects of individual antibias trainings on participants’ behavior are. In order to investigate this, participant observation in a qualitative pre–post setting was conducted, analyzing antibias training in an academic context. Two observers actively participated in the training sessions and documented the activities and reflection processes of the participants. Overall, the results question the effectiveness of single antibias trainings and show that a target-group adaptive approach is mandatory owing to the background of the approach in early childhood education. Therefore, antibias work needs to be adapted to the target group’s needs and realities of life. Furthermore, the study reveals that single antibias trainings must be embedded in a holistic diversity management approach to stimulate sustainable reflection processes among the target group. This article is one of the first to scientifically evaluate antibias training effectiveness, especially in engineering sciences and the university context.
Throughout the last decade, and particularly in 2022, water scarcity has become a critical concern in Morocco and other Mediterranean countries. The lack of rainfall during spring was worsened by a succession of heat waves during the summer. To address this drought, innovative solutions, including the use of new technologies such as hydrogels, will be essential to transform agriculture. This paper presents the findings of a study that evaluated the impact of hydrogel application on onion (Allium cepa) cultivation in Meknes, Morocco. The treatments investigated in this study comprised two different types of hydrogel-based soil additives (Arbovit® polyacrylate and Huminsorb® polyacrylate), applied at two rates (30 and 20 kg/ha), and irrigated at two levels of water supply (100% and 50% of daily crop evapotranspiration; ETc). Two control treatments were included, without hydrogel application and with both water amounts. The experiment was conducted in an open field using a completely randomized design. The results indicated a significant impact of both hydrogel-type dose and water dose on onion plant growth, as evidenced by various vegetation parameters. Among the hydrogels tested, Huminsorb® Polyacrylate produced the most favorable outcomes, with treatment T9 (100%, HP, 30 kg/ha) yielding 70.55 t/ha; this represented an increase of 11 t/ha as compared to the 100% ETc treatment without hydrogel application. Moreover, the combination of hydrogel application with 50% ETc water stress showed promising results, with treatment T4 (HP, 30 kg, 50%) producing almost the same yield as the 100% ETc treatment without hydrogel while saving 208 mm of water.
In times of short product life cycles, additive manufacturing and rapid tooling are important methods to make tool development and manufacturing more efficient. High-performance polymers are the key to mold production for prototypes and small series. However, the high temperatures during vulcanization injection molding cause thermal aging and can impair service life. The extent to which the thermal stress over the entire process chain stresses the material and whether it leads to irreversible material aging is evaluated. To this end, a mold made of PEEK is fabricated using fused filament fabrication and examined for its potential application. The mold is heated to 200 ◦C, filled with rubber, and cured. A differential scanning calorimetry analysis of each process step illustrates the crystallization behavior and first indicates the material resistance. It shows distinct cold crystallization regions at a build chamber temperature of 90 ◦C. At an ambient temperature above Tg, crystallization of 30% is achieved, and cold crystallization no longer occurs. Additional tensile tests show a decrease in tensile strength after ten days of thermal aging. The steady decrease in recrystallization temperature indicates degradation of the additives. However, the tensile tests reveal steady embrittlement of the material due to increasing crosslinking.
In addition to the technical content, modern courses at university should also teach professional skills to enhance the competencies of students towards their future work. The competency driven approach including technical as well as professional skills makes it necessary to find a suitable way for the integration into the corresponding module in a scalable and flexible manner. Agile development, for example, is essential for the development of modern systems and applications and makes use of dedicated professional skills of the team members, like structured group dynamics and communication, to enable the fast and reliable development. This paper presents an easy to integrate and flexible approach to integrate Scrum, an agile development method, into the lab of an existing module. Due to the different role models of Scrum the students have an individual learning success, gain valuable insight into modern system development and strengthen their communication and organization skills. The approach is implemented and evaluated in the module Vehicle Systems, but it can be transferred easily to other technical courses as well. The evaluation of the implementation considers feedback of all stakeholders, students, supervisor and lecturers, and monitors the observations during project lifetime.
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.
Melting probes are a proven tool for the exploration of thick ice layers and clean sampling of subglacial water on Earth. Their compact size and ease of operation also make them a key technology for the future exploration of icy moons in our Solar System, most prominently Europa and Enceladus. For both mission planning and hardware engineering, metrics such as efficiency and expected performance in terms of achievable speed, power requirements, and necessary heating power have to be known.
Theoretical studies aim at describing thermal losses on the one hand, while laboratory experiments and field tests allow an empirical investigation of the true performance on the other hand. To investigate the practical value of a performance model for the operational performance in extraterrestrial environments, we first contrast measured data from terrestrial field tests on temperate and polythermal glaciers with results from basic heat loss models and a melt trajectory model. For this purpose, we propose conventions for the determination of two different efficiencies that can be applied to both measured data and models. One definition of efficiency is related to the melting head only, while the other definition considers the melting probe as a whole. We also present methods to combine several sources of heat loss for probes with a circular cross-section, and to translate the geometry of probes with a non-circular cross-section to analyse them in the same way. The models were selected in a way that minimizes the need to make assumptions about unknown parameters of the probe or the ice environment.
The results indicate that currently used models do not yet reliably reproduce the performance of a probe under realistic conditions. Melting velocities and efficiencies are constantly overestimated by 15 to 50 % in the models, but qualitatively agree with the field test data. Hence, losses are observed, that are not yet covered and quantified by the available loss models. We find that the deviation increases with decreasing ice temperature. We suspect that this mismatch is mainly due to the too restrictive idealization of the probe model and the fact that the probe was not operated in an efficiency-optimized manner during the field tests. With respect to space mission engineering, we find that performance and efficiency models must be used with caution in unknown ice environments, as various ice parameters have a significant effect on the melting process. Some of these are difficult to estimate from afar.
This dataset was acquired at field tests of the steerable ice-melting probe "EnEx-IceMole" (Dachwald et al., 2014). A field test in summer 2014 was used to test the melting probe's system, before the probe was shipped to Antarctica, where, in international cooperation with the MIDGE project, the objective of a sampling mission in the southern hemisphere summer 2014/2015 was to return a clean englacial sample from the subglacial brine reservoir supplying the Blood Falls at Taylor Glacier (Badgeley et al., 2017, German et al., 2021).
The standardized log-files generated by the IceMole during melting operation include more than 100 operational parameters, housekeeping information, and error states, which are reported to the base station in intervals of 4 s. Occasional packet loss in data transmission resulted in a sparse number of increased sampling intervals, which where compensated for by linear interpolation during post processing. The presented dataset is based on a subset of this data: The penetration distance is calculated based on the ice screw drive encoder signal, providing the rate of rotation, and the screw's thread pitch. The melting speed is calculated from the same data, assuming the rate of rotation to be constant over one sampling interval. The contact force is calculated from the longitudinal screw force, which es measured by strain gauges. The used heating power is calculated from binary states of all heating elements, which can only be either switched on or off. Temperatures are measured at each heating element and averaged for three zones (melting head, side-wall heaters and back-plate heaters).
Manufacturing companies across multiple industries face an increasingly dynamic and unpredictable environment. This development can be seen on both the market and supply side. To respond to these challenges, manufacturing companies must implement smart manufacturing systems and become more flexible and agile. The flexibility in operational planning regarding the scheduling and sequencing of customer orders needs to be increased and new structures must be implemented in manufacturing systems’ fundamental design as they constitute much of the operational flexibility available. To this end, smart and more flexible solutions for production planning and control (PPC) are developed. However, scheduling or sequencing is often only considered isolated in a predefined stable environment. Moreover, their orientation on the fundamental logic of the existing IT solutions and their applicability in a dynamic environment is limited. This paper presents a conceptual model for a task-based description logic that can be applied to factory planning, technology planning, and operational control. By using service-oriented architectures, the goal is to generate smart manufacturing systems. The logic is designed to allow for easy and automated maintenance. It is compatible with the existing resource and process allocation logic across operational and strategic factory and production planning.
Traditional vulcanization mold manufacturing is complex, costly, and under pressure due to shorter product lifecycles and diverse variations. Additive manufacturing using Fused Filament Fabrication and high-performance polymers like PEEK offer a promising future in this industry. This study assesses the compressive strength of various infill structures (honeycomb, grid, triangle, cubic, and gyroid) when considering two distinct build directions (Z, XY) to enhance PEEK’s economic and resource efficiency in rapid tooling. A comparison with PETG samples shows the behavior of the infill strategies. Additionally, a proof of concept illustrates the application of a PEEK mold in vulcanization. A peak compressive strength of 135.6 MPa was attained in specimens that were 100% solid and subjected to thermal post-treatment. This corresponds to a 20% strength improvement in the Z direction. In terms of time and mechanical properties, the anisotropic grid and isotropic cubic infill have emerged for use in rapid tooling. Furthermore, the study highlights that reducing the layer thickness from 0.15 mm to 0.1 mm can result in a 15% strength increase. The study unveils the successful utilization of a room-temperature FFF-printed PEEK mold in vulcanization injection molding. The parameters and infill strategies identified in this research enable the resource-efficient FFF printing of PEEK without compromising its strength properties. Using PEEK in rapid tooling allows a cost reduction of up to 70% in tool production.
Achieving the 17 Sustainable Development Goals (SDGs) set by the United Nations (UN) in 2015 requires global collaboration between different stakeholders. Industry, and in particular engineers who shape industrial developments, have a special role to play as they are confronted with the responsibility to holistically reflect sustainability in industrial processes. This means that, in addition to the technical specifications, engineers must also question the effects of their own actions on an ecological, economic and social level in order to ensure sustainable action and contribute to the achievement of the SDGs. However, this requires competencies that enable engineers to apply all three pillars of sustainability to their own field of activity and to understand the global impact of industrial processes. In this context, it is relevant to understand how industry already reflects sustainability and to identify competences needed for sustainable development.
This book is based on a multimedia course for biological and chemical engineers, which is designed to trigger students' curiosity and initiative. A solid basic knowledge of thermodynamics and kinetics is necessary for understanding many technical, chemical, and biological processes.
The one-semester basic lecture course was divided into 12 workshops (chapters). Each chapter covers a practically relevant area of physical chemistry and contains the following didactic elements that make this book particularly exciting and understandable:
- Links to Videos at the start of each chapter as preparation for the workshop
- Key terms (in bold) for further research of your own
- Comprehension questions and calculation exercises with solutions as learning checks
- Key illustrations as simple, easy-to-replicate blackboard pictures
Humorous cartoons for each workshop (by Faelis) additionally lighten up the text and facilitate the learning process as a mnemonic. To round out the book, the appendix includes a summary of the most popular experiments in basic physical chemistry courses, as well as suggestions for designing workshops with exhibits, experiments, and "questions of the day."
Suitable for students minoring in chemistry; chemistry majors are sure to find this slimmed-down, didactically valuable book helpful as well. The book is excellent for self-study.
In times of social climate protection movements, such as Fridays for Future, the priorities of society, industry and higher education are currently changing. The consideration of sustainability challenges is increasing. In the context of sustainable development, social skills are crucial to achieving the United Nations Sustainable Development Goals (SDGs). In particular, the impact that educational activities have on people, communities and society is therefore coming to the fore. Research has shown that people with high levels of social competence are better able to manage stressful situations, maintain positive relationships and communicate effectively. They are also associated with better academic performance and career success. However, especially in engineering programs, the social pillar is underrepresented compared to the environmental and economic pillars.
In response to these changes, higher education institutions should be more aware of their social impact - from individual forms of teaching to entire modules and degree programs. To specifically determine the potential for improvement and derive resulting change for further development, we present an initial framework for social impact measurement by transferring already established approaches from the business sector to the education sector. To demonstrate the applicability, we measure the key competencies taught in undergraduate engineering programs in Germany.
The aim is to prepare the students for success in the modern world of work and their future contribution to sustainable development. Additionally, the university can include the results in its sustainability report. Our method can be applied to different teaching methods and enables their comparison.
Exposure to prolonged periods in microgravity is associated with deconditioning of the musculoskeletal system due to chronic changes in mechanical stimulation. Given astronauts will operate on the Lunar surface for extended periods of time, it is critical to quantify both external (e.g., ground reaction forces) and internal (e.g., joint reaction forces) loads of relevant movements performed during Lunar missions. Such knowledge is key to predict musculoskeletal deconditioning and determine appropriate exercise countermeasures associated with extended exposure to hypogravity.
This paper introduces an inexpensive Wiegand-sensor-based rotary encoder that avoids rotating magnets and is suitable for electrical-drive applications. So far, Wiegand-sensor-based encoders usually include a magnetic pole wheel with rotating permanent magnets. These encoders combine the disadvantages of an increased magnet demand and a limited maximal speed due to the centripetal force acting on the rotating magnets. The proposed approach reduces the total demand of permanent magnets drastically. Moreover, the rotating part is manufacturable from a single piece of steel, which makes it very robust and cheap. This work presents the theoretical operating principle of the proposed approach and validates its benefits on a hardware prototype. The presented proof-of-concept prototype achieves a mechanical resolution of 4.5 ° by using only 4 permanent magnets, 2Wiegand sensors and a rotating steel gear wheel with 20 teeth.
AI-based systems are nearing ubiquity not only in everyday low-stakes activities but also in medical procedures. To protect patients and physicians alike, explainability requirements have been proposed for the operation of AI-based decision support systems (AI-DSS), which adds hurdles to the productive use of AI in clinical contexts. This raises two questions: Who decides these requirements? And how should access to AI-DSS be provided to communities that reject these standards (particularly when such communities are expert-scarce)? This chapter investigates a dilemma that emerges from the implementation of global AI governance. While rejecting global AI governance limits the ability to help communities in need, global AI governance risks undermining and subjecting health-insecure communities to the force of the neo-colonial world order. For this, this chapter first surveys the current landscape of AI governance and introduces the approach of relational egalitarianism as key to (global health) justice. To discuss the two horns of the referred dilemma, the core power imbalances faced by health-insecure collectives (HICs) are examined. The chapter argues that only strong demands of a dual strategy towards health-secure collectives can both remedy the immediate needs of HICs and enable them to become healthcare independent.
Due to the decarbonization of the energy sector, the electric distribution grids are undergoing a major transformation, which is expected to increase the load on the operating resources due to new electrical loads and distributed energy resources. Therefore, grid operators need to gradually move to active grid management in order to ensure safe and reliable grid operation. However, this requires knowledge of key grid variables, such as node voltages, which is why the mass integration of measurement technology (smart meters) is necessary. Another problem is the fact that a large part of the topology of the distribution grids is not sufficiently digitized and models are partly faulty, which means that active grid operation management today has to be carried out largely blindly. It is therefore part of current research to develop methods for determining unknown grid topologies based on measurement data. In this paper, different clustering algorithms are presented and their performance of topology detection of low voltage grids is compared. Furthermore, the influence of measurement uncertainties is investigated in the form of a sensitivity analysis.
Autonomous agents require rich environment models for fulfilling their missions. High-definition maps are a well-established map format which allows for representing semantic information besides the usual geometric information of the environment. These are, for instance, road shapes, road markings, traffic signs or barriers. The geometric resolution of HD maps can be as precise as of centimetre level. In this paper, we report on our approach of using HD maps as a map representation for autonomous load-haul-dump vehicles in open-pit mining operations. As the mine undergoes constant change, we also need to constantly update the map. Therefore, we follow a lifelong mapping approach for updating the HD maps based on camera-based object detection and GPS data. We show our mapping algorithm based on the Lanelet 2 map format and show our integration with the navigation stack of the Robot Operating System. We present experimental results on our lifelong mapping approach from a real open-pit mine.
Anti-bias trainings are increasingly demanded and practiced in academia and industry to increase employees’ sensitivity to discrimination, racism, and diversity. Under the heading of “Diversity Management”, anti-bias trainings are mainly offered as one-off workshops intending to raise awareness of unconscious biases, create a diversity-affirming corporate culture, awake awareness of the potential of diversity, and ultimately enable the reflection of diversity in development processes. However, coming from childhood education, research and scientific articles on the sustainable effectiveness of anti-bias in adulthood, especially in academia, are very scarce. In order to fill this research gap, the paper explores how sustainable the effects of individual anti-bias trainings on the behavior of participants are. In order to investigate this, participant observation in a qualitative pre-post setting was conducted, analyzing anti-bias trainings in an academic context. Two observers actively participated in the training sessions and documented the activities and reflection processes of the participants. Overall, the results question the effectiveness of single anti-bias trainings and show that a target-group adaptive approach is mandatory due to the background of the approach in early childhood education. Therefore, it can be concluded that anti-bias work needs to be adapted to the target group’s needs and reality of life. Furthermore, the study reveals that single anti-bias trainings must be embedded in a holistic diversity management approach to stimulate sustainable reflection processes among the target group. This paper is one of the first to scientifically evaluate anti-bias training effectiveness, especially in engineering sciences and the university context.
Ceramic hot gas filters are widely used in combined cycles based on pressurised fluidised beds. They fulfil most of the demands with respect to cleaning efficiency and long time durability, but their operation regarding the consumption of pulse gas and energy still has to be optimised. Experimental investigations were carried out to measure the flow field, the pressure and the gas temperature inside the filter candle during pulse jet cleaning. These results are compared with the results of a numerical procedure based on a solution of the two - dimensional conservation equations for momentum and energy. The observed difficulties handling different flow regimes like highly turbulent flow as well as Darcy flow simultaneously are discussed.
The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis. Automated speaker attribution, which detects who said what to whom in a speech event and is closely related to semantic role labeling, is an important processing step for computational text analysis. We study the potential of the large language model family Llama 2 to automate speaker attribution in German parliamentary debates from 2017-2021. We fine-tune Llama 2 with QLoRA, an efficient training strategy, and observe our approach to achieve competitive performance in the GermEval 2023 Shared Task On Speaker Attribution in German News Articles and Parliamentary Debates. Our results shed light on the capabilities of large language models in automating speaker attribution, revealing a promising avenue for computational analysis of political discourse and the development of semantic role labeling systems.
Software development projects often fail because of insufficient code quality. It is now well documented that the task of testing software, for example, is perceived as uninteresting and rather boring, leading to poor software quality and major challenges to software development companies. One promising approach to increase the motivation for considering software quality is the use of gamification. Initial research works already investigated the effects of gamification on software developers and come to promising. Nevertheless, a lack of results from field experiments exists, which motivates the chapter at hand. By conducting a gamification experiment with five student software projects and by interviewing the project members, the chapter provides insights into the changing programming behavior of information systems students when confronted with a leaderboard. The results reveal a motivational effect as well as a reduction of code smells.
Immunosorbent turnip vein clearing virus (TVCV) particles displaying the IgG-binding domains D and E of Staphylococcus aureus protein A (PA) on every coat protein (CP) subunit (TVCVPA) were purified from plants via optimized and new protocols. The latter used polyethylene glycol (PEG) raw precipitates, from which virions were selectively re-solubilized in reverse PEG concentration gradients. This procedure improved the integrity of both TVCVPA and the wild-type subgroup 3 tobamovirus. TVCVPA could be loaded with more than 500 IgGs per virion, which mediated the immunocapture of fluorescent dyes, GFP, and active enzymes. Bi-enzyme ensembles of cooperating glucose oxidase and horseradish peroxidase were tethered together on the TVCVPA carriers via a single antibody type, with one enzyme conjugated chemically to its Fc region, and the other one bound as a target, yielding synthetic multi-enzyme complexes. In microtiter plates, the TVCVPA-displayed sugar-sensing system possessed a considerably increased reusability upon repeated testing, compared to the IgG-bound enzyme pair in the absence of the virus. A high coverage of the viral adapters was also achieved on Ta2O5 sensor chip surfaces coated with a polyelectrolyte interlayer, as a prerequisite for durable TVCVPA-assisted electrochemical biosensing via modularly IgG-assembled sensor enzymes.
Hydrogen peroxide (H₂O₂), a strong oxidizer, is a commonly used sterilization agent employed during aseptic food processing and medical applications. To assess the sterilization efficiency with H₂O₂, bacterial spores are common microbial systems due to their remarkable robustness against a wide variety of decontamination strategies. Despite their widespread use, there is, however, only little information about the detailed time-resolved mechanism underlying the oxidative spore death by H₂O₂. In this work, we investigate chemical and morphological changes of individual Bacillus atrophaeus spores undergoing oxidative damage using optical sensing with trapping Raman microscopy in real-time. The time-resolved experiments reveal that spore death involves two distinct phases: (i) an initial phase dominated by the fast release of dipicolinic acid (DPA), a major spore biomarker, which indicates the rupture of the spore’s core; and (ii) the oxidation of the remaining spore material resulting in the subsequent fragmentation of the spores’ coat. Simultaneous observation of the spore morphology by optical microscopy corroborates these mechanisms. The dependence of the onset of DPA release and the time constant of spore fragmentation on H₂O₂ shows that the formation of reactive oxygen species from H₂O₂ is the rate-limiting factor of oxidative spore death.
Clinical assessment of newly developed sensors is important for ensuring their validity. Comparing recordings of emerging electrocardiography (ECG) systems to a reference ECG system requires accurate synchronization of data from both devices. Current methods can be inefficient and prone to errors. To address this issue, three algorithms are presented to synchronize two ECG time series from different recording systems: Binned R-peak Correlation, R-R Interval Correlation, and Average R-peak Distance. These algorithms reduce ECG data to their cyclic features, mitigating inefficiencies and minimizing discrepancies between different recording systems. We evaluate the performance of these algorithms using high-quality data and then assess their robustness after manipulating the R-peaks. Our results show that R-R Interval Correlation was the most efficient, whereas the Average R-peak Distance and Binned R-peak Correlation were more robust against noisy data.
We present first results from a newly developed monitoring station for a closed loop geothermal heat pump test installation at our campus, consisting of helix coils and plate heat exchangers, as well as an ice-store system. There are more than 40 temperature sensors and several soil moisture content sensors distributed around the system, allowing a detailed monitoring under different operating conditions.In the view of the modern development of renewable energies along with the newly concepts known as Internet of Things and Industry 4.0 (high-tech strategy from the German government), we created a user-friendly web application, which will connect the things (sensors) with the open network (www). Besides other advantages, this allows a continuous remote monitoring of the data from the numerous sensors at an arbitrary sampling rate.Based on the recorded data, we will also present first results from numerical simulations, taking into account all relevant heat transport processes.The aim is to improve the understanding of these processes and their influence on the thermal behavior of shallow geothermal systems in the unsaturated zone. This will in turn facilitate the prediction of the performance of these systems and therefore yield an improvement in their dimensioning when designing a specific shallow geothermal installation.
The first and last mile of a railway journey, in both freight and transit applications, constitutes a high effort and is either non-productive (e.g. in the case of depot operations) or highly inefficient (e.g. in industrial railways). These parts are typically managed on-sight, i.e. with no signalling and train protection systems ensuring the freedom of movement. This is possible due to the rather short braking distances of individual vehicles and shunting consists. The present article analyses the braking behaviour of such shunting units. For this purpose, a dedicated model is developed. It is calibrated on published results of brake tests and validated against a high-definition model for low-speed applications. Based on this model, multiple simulations are executed to obtain a Monte Carlo simulation of the resulting braking distances. Based on the distribution properties and established safety levels, the risk of exceeding certain braking distances is evaluated and maximum braking distances are derived. Together with certain parameters of the system, these can serve in the design and safety assessment of driver assistance systems and automation of these processes.
The problem of fair and privacy-preserving ordered set reconciliation arises in a variety of applications like auctions, e-voting, and appointment reconciliation. While several multi-party protocols have been proposed that solve this problem in the semi-honest model, there are no multi-party protocols that are secure in the malicious model so far. In this paper, we close this gap. Our newly proposed protocols are shown to be secure in the malicious model based on a variety of novel non-interactive zero-knowledge-proofs. We describe the implementation of our protocols and evaluate their performance in comparison to protocols solving the problem in the semi-honest case.
Prioritization is an essential task within requirements engineering to cope with complexity and to establish focus properly. The 3rd Workshop on Requirements Prioritization for customer oriented Software Development (RePriCo’12) focused on requirements prioritization and adjacent themes in the context of customer oriented development of bespoke and standard software. Five submissions have been accepted for the proceedings and for presentation. The report summarizes and points out key findings.
The RoboCup Logistics League (RCLL) is a robotics competition in a production logistics scenario in the context of a Smart Factory. In the competition, a team of three robots needs to assemble products to fulfill various orders that are requested online during the game. This year, the Carologistics team was able to win the competition with a new approach to multi-agent coordination as well as significant changes to the robot’s perception unit and a pragmatic network setup using the cellular network instead of WiFi. In this paper, we describe the major components of our approach with a focus on the changes compared to the last physical competition in 2019.
Due to the increasing complexity of software projects, software development is becoming more and more dependent on teams. The quality of this teamwork can vary depending on the team composition, as teams are always a combination of different skills and personality types. This paper aims to answer the question of how to describe a software development team and what influence the personality of the team members has on the team dynamics. For this purpose, a systematic literature review (n=48) and a literature search with the AI research assistant Elicit (n=20) were conducted. Result: A person’s personality significantly shapes his or her thinking and actions, which in turn influences his or her behavior in software development teams. It has been shown that team performance and satisfaction can be strongly influenced by personality. The quality of communication and the likelihood of conflict can also be attributed to personality.
This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products.
Experimental determination of the cross sections of proton capture on radioactive nuclei is extremely difficult. Therefore, it is of substantial interest for the understanding of the production of the p-nuclei. For the first time, a direct measurement of proton-capture cross sections on stored, radioactive ions became possible in an energy range of interest for nuclear astrophysics. The experiment was performed at the Experimental Storage Ring (ESR) at GSI by making use of a sensitive method to measure (p,γ) and (p,n) reactions in inverse kinematics. These reaction channels are of high relevance for the nucleosyn-thesis processes in supernovae, which are among the most violent explosions in the universe and are not yet well understood. The cross section of the ¹¹⁸Te(p,γ) reaction has been measured at energies of 6 MeV/u and 7 MeV/u. The heavy ions interacted with a hydrogen gas jet target. The radiative recombination process of the fully stripped ¹¹⁸Te ions and electrons from the hydrogen target was used as a luminosity monitor. An overview of the experimental method and preliminary results from the ongoing analysis will be presented.
Digital forensics of smartphones is of utmost importance in many criminal cases. As modern smartphones store chats, photos, videos etc. that can be relevant for investigations and as they can have storage capacities of hundreds of gigabytes, they are a primary target for forensic investigators. However, it is exactly this large amount of data that is causing problems: extracting and examining the data from multiple phones seized in the context of a case is taking more and more time. This bears the risk of wasting a lot of time with irrelevant phones while there is not enough time left to analyze a phone which is worth examination. Forensic triage can help in this case: Such a triage is a preselection step based on a subset of data and is performed before fully extracting all the data from the smartphone. Triage can accelerate subsequent investigations and is especially useful in cases where time is essential. The aim of this paper is to determine which and how much data from an Android smartphone can be made directly accessible to the forensic investigator – without tedious investigations. For this purpose, an app has been developed that can be used with extremely limited storage of data in the handset and which outputs the extracted data immediately to the forensic workstation in a human- and machine-readable format.
The worldwide Corona pandemic has severely restricted student projects in the higher semesters of engineering courses. In order not to delay the graduation, a new concept had to be developed for projects under lockdown conditions. Therefore, unused rooms at the university should be digitally recorded in order to develop a new usage concept as laboratory rooms. An inventory of the actual state of the rooms was done first by taking photos and listing up all flaws and peculiarities. After that, a digital site measuring was done with a 360° laser scanner and these recorded scans were linked to a coherent point cloud and transferred to a software for planning technical building services and supporting Building Information Modelling (BIM). In order to better illustrate the difference between the actual and target state, two virtual reality models were created for realistic demonstration. During the project, the students had to go through the entire digital planning phases. Technical specifications had to be complied with, as well as documentation, time planning and cost estimate. This project turned out to be an excellent alternative to on-site practical training under lockdown conditions and increased the students’ motivation to deal with complex technical questions.
In the context of the Corona pandemic and its impact on teaching like digital lectures and exercises a new concept especially for freshmen in demanding courses of Smart Building Engineering became necessary. As there were hardly any face-to-face events at the university, the new teaching concept should enable a good start into engineering studies under pandemic conditions anyway and should also replace the written exam at the end. The students should become active themselves in small teams instead of listening passively to a lecture broadcast online with almost no personal contact. For this purpose, a role play was developed in which the freshmen had to work out a complete solution to the realistic problem of designing, construction planning and implementing a small guesthouse. Each student of the team had to take a certain role like architect, site manager, BIM-manager, electrician and the technitian for HVAC installations. Technical specifications must be complied with, as well as documentation, time planning and cost estimate. The final project folder had to contain technical documents like circuit diagrams for electrical components, circuit diagrams for water and heating, design calculations and components lists. On the other hand construction schedule, construction implementation plan, documentation of the construction progress and minutes of meetings between the various trades had to be submitted as well. In addition to the project folder, a model of the construction project must also be created either as a handmade model or as a digital 3D-model using Computer-aided design (CAD) software. The first steps in the field of Building information modelling (BIM) had also been taken by creating a digital model of the building showing the current planning status in real time as a digital twin. This project turned out to be an excellent training of important student competencies like teamwork, communication skills, and self -organisation and also increased motivation to work on complex technical questions. The aim of giving the student a first impression on the challenges and solutions in building projects with many different technical trades and their points of view was very well achieved and should be continued in the future.
Selected problems in the field of multivariate statistical analysis are treated. Thereby, one focus is on the paired sample case. Among other things, statistical testing problems of marginal homogeneity are under consideration. In detail, properties of Hotelling‘s T² test in a special parametric situation are obtained. Moreover, the nonparametric problem of marginal homogeneity is discussed on the basis of possibly incomplete data. In the bivariate data case, properties of the Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic on the basis of partly not identically distributed data are investigated. Similar testing problems are treated within the scope of the application of a result for the empirical process of the concomitants for partly categorial data. Furthermore, testing changes in the modeled solvency capital requirement of an insurance company by means of a paired sample from an internal risk model is discussed. Beyond the paired sample case, a new asymptotic relative efficiency concept based on the expected volumes of multidimensional confidence regions is introduced. Besides, a new approach for the treatment of the multi-sample goodness-of-fit problem is presented. Finally, a consistent test for the treatment of the goodness-of-fit problem is developed for the background of huge or infinite dimensional data.
KNX is a protocol for smart building automation, e.g., for automated heating, air conditioning, or lighting. This paper analyses and evaluates state-of-the-art KNX devices from manufacturers Merten, Gira and Siemens with respect to security. On the one hand, it is investigated if publicly known vulnerabilities like insecure storage of passwords in software, unencrypted communication, or denialof-service attacks, can be reproduced in new devices. On the other hand, the security is analyzed in general, leading to the discovery of a previously unknown and high risk vulnerability related to so-called BCU (authentication) keys.
Nowadays, the most employed devices for recoding videos or capturing images are undoubtedly the smartphones. Our work investigates the application of source camera identification on mobile phones. We present a dataset entirely collected by mobile phones. The dataset contains both still images and videos collected by 67 different smartphones. Part of the images consists in photos of uniform backgrounds, especially collected for the computation of the RSPN. Identifying the source camera given a video is particularly challenging due to the strong video compression. The experiments reported in this paper, show the large variation in performance when testing an highly accurate technique on still images and videos.
Even the shortest flight through unknown, cluttered environments requires reliable local path planning algorithms to avoid unforeseen obstacles. The algorithm must evaluate alternative flight paths and identify the best path if an obstacle blocks its way. Commonly, weighted sums are used here. This work shows that weighted Chebyshev distances and factorial achievement scalarising functions are suitable alternatives to weighted sums if combined with the 3DVFH* local path planning algorithm. Both methods considerably reduce the failure probability of simulated flights in various environments. The standard 3DVFH* uses a weighted sum and has a failure probability of 50% in the test environments. A factorial achievement scalarising function, which minimises the worst combination of two out of four objective functions, reaches a failure probability of 26%; A weighted Chebyshev distance, which optimises the worst objective, has a failure probability of 30%. These results show promise for further enhancements and to support broader applicability.
Ice melting probes
(2023)
The exploration of icy environments in the solar system, such as the poles of Mars and the icy moons (a.k.a. ocean worlds), is a key aspect for understanding their astrobiological potential as well as for extraterrestrial resource inspection. On these worlds, ice melting probes are considered to be well suited for the robotic clean execution of such missions. In this chapter, we describe ice melting probes and their applications, the physics of ice melting and how the melting behavior can be modeled and simulated numerically, the challenges for ice melting, and the required key technologies to deal with those challenges. We also give an overview of existing ice melting probes and report some results and lessons learned from laboratory and field tests.
Lead and nickel, as heavy metals, are still used in industrial processes, and are classified as “environmental health hazards” due to their toxicity and polluting potential. The detection of heavy metals can prevent environmental pollution at toxic levels that are critical to human health. In this sense, the electrolyte–insulator–semiconductor (EIS) field-effect sensor is an attractive sensing platform concerning the fabrication of reusable and robust sensors to detect such substances. This study is aimed to fabricate a sensing unit on an EIS device based on Sn₃O₄ nanobelts embedded in a polyelectrolyte matrix of polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) using the layer-by-layer (LbL) technique. The EIS-Sn₃O₄ sensor exhibited enhanced electrochemical performance for detecting Pb²⁺ and Ni²⁺ ions, revealing a higher affinity for Pb²⁺ ions, with sensitivities of ca. 25.8 mV/decade and 2.4 mV/decade, respectively. Such results indicate that Sn₃O₄ nanobelts can contemplate a feasible proof-of-concept capacitive field-effect sensor for heavy metal detection, envisaging other future studies focusing on environmental monitoring.
Automated driving is now possible in diverse road and traffic conditions. However, there are still situations that automated vehicles cannot handle safely and efficiently. In this case, a Transition of Control (ToC) is necessary so that the driver takes control of the driving. Executing a ToC requires the driver to get full situation awareness of the driving environment. If the driver fails to get back the control in a limited time, a Minimum Risk Maneuver (MRM) is executed to bring the vehicle into a safe state (e.g., decelerating to full stop). The execution of ToCs requires some time and can cause traffic disruption and safety risks that increase if several vehicles execute ToCs/MRMs at similar times and in the same area. This study proposes to use novel C-ITS traffic management measures where the infrastructure exploits V2X communications to assist Connected and Automated Vehicles (CAVs) in the execution of ToCs. The infrastructure can suggest a spatial distribution of ToCs, and inform vehicles of the locations where they could execute a safe stop in case of MRM. This paper reports the first field operational tests that validate the feasibility and quantify the benefits of the proposed infrastructure-assisted ToC and MRM management. The paper also presents the CAV and roadside infrastructure prototypes implemented and used in the trials. The conducted field trials demonstrate that infrastructure-assisted traffic management solutions can reduce safety risks and traffic disruptions.
Modern implementations of driver assistance systems are evolving from a pure driver assistance to a independently acting automation system. Still these systems are not covering the full vehicle usage range, also called operational design domain, which require the human driver as fall-back mechanism. Transition of control and potential minimum risk manoeuvres are currently research topics and will bridge the gap until full autonomous vehicles are available. The authors showed in a demonstration that the transition of control mechanisms can be further improved by usage of communication technology. Receiving the incident type and position information by usage of standardised vehicle to everything (V2X) messages can improve the driver safety and comfort level. The connected and automated vehicle’s software framework can take this information to plan areas where the driver should take back control by initiating a transition of control which can be followed by a minimum risk manoeuvre in case of an unresponsive driver. This transition of control has been implemented in a test vehicle and was presented to the public during the IEEE IV2022 (IEEE Intelligent Vehicle Symposium) in Aachen, Germany.
Deammonification for nitrogen removal in municipal wastewater in temperate and cold climate zones is currently limited to the side stream of municipal wastewater treatment plants (MWWTP). This study developed a conceptual model of a mainstream deammonification plant, designed for 30,000 P.E., considering possible solutions corresponding to the challenging mainstream conditions in Germany. In addition, the energy-saving potential, nitrogen elimination performance and construction-related costs of mainstream deammonification were compared to a conventional plant model, having a single-stage activated sludge process with upstream denitrification. The results revealed that an additional treatment step by combining chemical precipitation and ultra-fine screening is advantageous prior the mainstream deammonification. Hereby chemical oxygen demand (COD) can be reduced by 80% so that the COD:N ratio can be reduced from 12 to 2.5. Laboratory experiments testing mainstream conditions of temperature (8–20°C), pH (6–9) and COD:N ratio (1–6) showed an achievable volumetric nitrogen removal rate (VNRR) of at least 50 gN/(m3∙d) for various deammonifying sludges from side stream deammonification systems in the state of North Rhine-Westphalia, Germany, where m3 denotes reactor volume. Assuming a retained Norganic content of 0.0035 kgNorg./(P.E.∙d) from the daily loads of N at carbon removal stage and a VNRR of 50 gN/(m3∙d) under mainstream conditions, a resident-specific reactor volume of 0.115 m3/(P.E.) is required for mainstream deammonification. This is in the same order of magnitude as the conventional activated sludge process, i.e., 0.173 m3/(P.E.) for an MWWTP of size class of 4. The conventional plant model yielded a total specific electricity demand of 35 kWh/(P.E.∙a) for the operation of the whole MWWTP and an energy recovery potential of 15.8 kWh/(P.E.∙a) through anaerobic digestion. In contrast, the developed mainstream deammonification model plant would require only a 21.5 kWh/(P.E.∙a) energy demand and result in 24 kWh/(P.E.∙a) energy recovery potential, enabling the mainstream deammonification model plant to be self-sufficient. The retrofitting costs for the implementation of mainstream deammonification in existing conventional MWWTPs are nearly negligible as the existing units like activated sludge reactors, aerators and monitoring technology are reusable. However, the mainstream deammonification must meet the performance requirement of VNRR of about 50 gN/(m3∙d) in this case.
Digital twins are seen as one of the key technologies of Industry 4.0. Although many research groups focus on digital twins and create meaningful outputs, the technology has not yet reached a broad application in the industry. The main reasons for this imbalance are the complexity of the topic, the lack of specialists, and the unawareness of the twin opportunities. The project "Digital Twin Academy" aims to overcome these barriers by focusing on three actions: Building a digital twin community for discussion and exchange, offering multi-stage training for various knowledge levels, and implementing realworld use cases for deeper insights and guidance. In this work, we focus on creating a flexible learning platform that allows the user to select a training path adjusted to personal knowledge and needs. Therefore, a mix of basic and advanced modules is created and expanded by individual feedback options. The usage of personas supports the selection of the appropriate modules.
The development of protype applications with sensors and actuators in the automation industry requires tools that are independent of manufacturer, and are flexible enough to be modified or extended for any specific requirements. Currently, developing prototypes with industrial sensors and actuators is not straightforward. First of all, the exchange of information depends on the industrial protocol that these devices have. Second, a specific configuration and installation is done based on the hardware that is used, such as automation controllers or industrial gateways. This means that the development for a specific industrial protocol, highly depends on the hardware and the software that vendors provide. In this work we propose a rapid-prototyping framework based on Arduino to solve this problem. For this project we have focused to work with the IO-Link protocol. The framework consists of an Arduino shield that acts as the physical layer, and a software that implements the IO-Link Master protocol. The main advantage of such framework is that an application with industrial devices can be rapid-prototyped with ease as its vendor independent, open-source and can be ported easily to other Arduino compatible boards. In comparison, a typical approach requires proprietary hardware, is not easy to port to another system and is closed-source.
Background
Post-COVID-19 syndrome (PCS) is a lingering disease with ongoing symptoms such as fatigue and cognitive impairment resulting in a high impact on the daily life of patients. Understanding the pathophysiology of PCS is a public health priority, as it still poses a diagnostic and treatment challenge for physicians.
Methods
In this prospective observational cohort study, we analyzed the retinal microcirculation using Retinal Vessel Analysis (RVA) in a cohort of patients with PCS and compared it to an age- and gender-matched healthy cohort (n = 41, matched out of n = 204).
Measurements and main results
PCS patients exhibit persistent endothelial dysfunction (ED), as indicated by significantly lower venular flicker-induced dilation (vFID; 3.42% ± 1.77% vs. 4.64% ± 2.59%; p = 0.02), narrower central retinal artery equivalent (CRAE; 178.1 [167.5–190.2] vs. 189.1 [179.4–197.2], p = 0.01) and lower arteriolar-venular ratio (AVR; (0.84 [0.8–0.9] vs. 0.88 [0.8–0.9], p = 0.007). When combining AVR and vFID, predicted scores reached good ability to discriminate groups (area under the curve: 0.75). Higher PCS severity scores correlated with lower AVR (R = − 0.37 p = 0.017). The association of microvascular changes with PCS severity were amplified in PCS patients exhibiting higher levels of inflammatory parameters.
Conclusion
Our results demonstrate that prolonged endothelial dysfunction is a hallmark of PCS, and impairments of the microcirculation seem to explain ongoing symptoms in patients. As potential therapies for PCS emerge, RVA parameters may become relevant as clinical biomarkers for diagnosis and therapy management.
Preprint: Studies on the enzymatic reduction of levulinic acid using Chiralidon-R and Chiralidon-S
(2023)
The enzymatic reduction of levulinic acid by the chiral catalysts Chiralidon-R and Chiralidon-S which are commercially available superabsorbed alcohol dehydrogenases is described. The Chiralidon®-R/S reduces the levulinic acid to the (R,S)-4-hydroxy valeric acid and the (R)- or (S)- gamma-valerolactone.
In recent years, the development of large pretrained language models, such as BERT and GPT, significantly improved information extraction systems on various tasks, including relation classification. State-of-the-art systems are highly accurate on scientific benchmarks. A lack of explainability is currently a complicating factor in many real-world applications. Comprehensible systems are necessary to prevent biased, counterintuitive, or harmful decisions.
We introduce semantic extents, a concept to analyze decision patterns for the relation classification task. Semantic extents are the most influential parts of texts concerning classification decisions. Our definition allows similar procedures to determine semantic extents for humans and models. We provide an annotation tool and a software framework to determine semantic extents for humans and models conveniently and reproducibly. Comparing both reveals that models tend to learn shortcut patterns from data. These patterns are hard to detect with current interpretability methods, such as input reductions. Our approach can help detect and eliminate spurious decision patterns during model development. Semantic extents can increase the reliability and security of natural language processing systems. Semantic extents are an essential step in enabling applications in critical areas like healthcare or finance. Moreover, our work opens new research directions for developing methods to explain deep learning models.
Extracting workflow nets from textual descriptions can be used to simplify guidelines or formalize textual descriptions of formal processes like business processes and algorithms. The task of manually extracting processes, however, requires domain expertise and effort. While automatic process model extraction is desirable, annotating texts with formalized process models is expensive. Therefore, there are only a few machine-learning-based extraction approaches. Rule-based approaches, in turn, require domain specificity to work well and can rarely distinguish relevant and irrelevant information in textual descriptions. In this paper, we present GUIDO, a hybrid approach to the process model extraction task that first, classifies sentences regarding their relevance to the process model, using a BERT-based sentence classifier, and second, extracts a process model from the sentences classified as relevant, using dependency parsing. The presented approach achieves significantly better resul ts than a pure rule-based approach. GUIDO achieves an average behavioral similarity score of 0.93. Still, in comparison to purely machine-learning-based approaches, the annotation costs stay low.
Providing healthcare services frequently involves cognitively demanding tasks, including diagnoses and analyses as well as complex decisions about treatments and therapy. From a global perspective, ethically significant inequalities exist between regions where the expert knowledge required for these tasks is scarce or abundant. One possible strategy to diminish such inequalities and increase healthcare opportunities in expert-scarce settings is to provide healthcare solutions involving digital technologies that do not necessarily require the presence of a human expert, e.g., in the form of artificial intelligent decision-support systems (AI-DSS). Such algorithmic decision-making, however, is mostly developed in resource- and expert-abundant settings to support healthcare experts in their work. As a practical consequence, the normative standards and requirements for such algorithmic decision-making in healthcare require the technology to be at least as explainable as the decisions made by the experts themselves. The goal of providing healthcare in settings where resources and expertise are scarce might come with a normative pull to lower the normative standards of using digital technologies in order to provide at least some healthcare in the first place. We scrutinize this tendency to lower standards in particular settings from a normative perspective, distinguish between different types of absolute and relative, local and global standards of explainability, and conclude by defending an ambitious and practicable standard of local relative explainability.
The work in modern open-pit and underground mines requires the transportation of large amounts of resources between fixed points. The navigation to these fixed points is a repetitive task that can be automated. The challenge in automating the navigation of vehicles commonly used in mines is the systemic properties of such vehicles. Many mining vehicles, such as the one we have used in the research for this paper, use steering systems with an articulated joint bending the vehicle’s drive axis to change its course and a hydraulic drive system to actuate axial drive components or the movements of tippers if available. To address the difficulties of controlling such a vehicle, we present a model-predictive approach for controlling the vehicle. While the control optimisation based on a parallel error minimisation of the predicted state has already been established in the past, we provide insight into the design and implementation of an MPC for an articulated mining vehicle and show the results of real-world experiments in an open-pit mine environment.
Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance.
However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP.
The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework.
Messenger apps like WhatsApp and Telegram are frequently used for everyday communication, but they can also be utilized as a platform for illegal activity. Telegram allows public groups with up to 200.000 participants. Criminals use these public groups for trading illegal commodities and services, which becomes a concern for law enforcement agencies, who manually monitor suspicious activity in these chat rooms. This research demonstrates how natural language processing (NLP) can assist in analyzing these chat rooms, providing an explorative overview of the domain and facilitating purposeful analyses of user behavior. We provide a publicly available corpus of annotated text messages with entities and relations from four self-proclaimed black market chat rooms. Our pipeline approach aggregates the extracted product attributes from user messages to profiles and uses these with their sold products as features for clustering. The extracted structured information is the foundation for further data exploration, such as identifying the top vendors or fine-granular price analyses. Our evaluation shows that pretrained word vectors perform better for unsupervised clustering than state-of-the-art transformer models, while the latter is still superior for sequence labeling.
To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15% more efficiently by 2025 and 30% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the long-haul application. The resulting hybrid electric vehicle (HEV) truck gains most of the fuel saving potential by the recuperation of potential energy and its consecutive utilization. The key to utilizing the full potential of HEV-HD trucks is to maximize the amount of recuperated energy and ensure its intelligent usage while keeping the operating point of the internal combustion engine as efficient as possible. To achieve this goal, an intelligent energy management strategy (EMS) based on ECMS is developed for a parallel HEV-HD truck which uses predictive discharge of the battery and adaptive operating strategy regarding the height profile and the vehicle mass. The presented EMS can reproduce the global optimal operating strategy over long phases and lead to a fuel saving potential of up to 2% compared with a heuristic strategy. Furthermore, the fuel saving potential is correlated with the investigated boundary conditions to deepen the understanding of the impact of intelligent EMS for HEV-HD trucks.
The connective tissues such as tendons contain an extracellular matrix (ECM) comprising collagen fibrils scattered within the ground substance. These fibrils are instrumental in lending mechanical stability to tissues. Unfortunately, our understanding of how collagen fibrils reinforce the ECM remains limited, with no direct experimental evidence substantiating current theories. Earlier theoretical studies on collagen fibril reinforcement in the ECM have relied predominantly on the assumption of uniform cylindrical fibers, which is inadequate for modelling collagen fibrils, which possessed tapered ends. Recently, Topçu and colleagues published a paper in the International Journal of Solids and Structures, presenting a generalized shear-lag theory for the transfer of elastic stress between the matrix and fibers with tapered ends. This paper is a positive step towards comprehending the mechanics of the ECM and makes a valuable contribution to formulating a complete theory of collagen fibril reinforcement in the ECM.
Even though BIM (Building Information Modelling) is successfully implemented in most of the world, it is still in the early stages in Germany, since the stakeholders are sceptical of its reliability and efficiency. The purpose of this paper is to analyse the opportunities and obstacles to implementing BIM for prefabrication. Among all other advantages of BIM, prefabrication is chosen for this paper because it plays a vital role in creating an impact on the time and cost factors of a construction project. The project stakeholders and participants can explicitly observe the positive impact of prefabrication, which enables the breakthrough of the scepticism factor among the small-scale construction companies. The analysis consists of the development of a process workflow for implementing prefabrication in building construction followed by a practical approach, which was executed with two case studies. It was planned in such a way that, the first case study gives a first-hand experience for the workers at the site on the BIM model so that they can make much use of the created BIM model, which is a better representation compared to the traditional 2D plan. The main aim of the first case study is to create a belief in the implementation of BIM Models, which was succeeded by the execution of offshore prefabrication in the second case study. Based on the case studies, the time analysis was made and it is inferred that the implementation of BIM for prefabrication can reduce construction time, ensures minimal wastes, better accuracy, less problem-solving at the construction site. It was observed that this process requires more planning time, better communication between different disciplines, which was the major obstacle for successful implementation. This paper was carried out from the perspective of small and medium-sized mechanical contracting companies for the private building sector in Germany.
Urban farming is an innovative and sustainable way of food production and is becoming more and more important in smart city and quarter concepts. It also enables the production of certain foods in places where they usually dare not produced, such as production of fish or shrimps in large cities far away from the coast. Unfortunately, it is not always possible to show students such concepts and systems in real life as part of courses: visits of such industry plants are sometimes not possible because of distance or are permitted by the operator for hygienic reasons. In order to give the students the opportunity of getting into contact with such an urban farming system and its complex operation, an industrial urban farming plant was set up on a significantly smaller scale. Therefore, all needed technical components like water aeriation, biological and mechanical filtration or water circulation have been replaced either by aquarium components or by self-designed parts also using a 3D-printer. Students from different courses like mechanical engineering, smart building engineering, biology, electrical engineering, automation technology and civil engineering were involved in this project. This “miniature industrial plant” was also able to start operation and has now been running for two years successfully. Due to Corona pandemic, home office and remote online lectures, the automation of this miniature plant should be brought to a higher level in future for providing a good control over the system and water quality remotely. The aim of giving the student a chance to get to know the operation of an urban farming plant was very well achieved and the students had lots of fun in “playing” and learning with it in a realistic way.
Using scenarios is vital in identifying and specifying measures for successfully transforming the energy system. Such transformations can be particularly challenging and require the support of a broader set of stakeholders. Otherwise, there will be opposition in the form of reluctance to adopt the necessary technologies. Usually, processes for considering stakeholders' perspectives are very time-consuming and costly. In particular, there are uncertainties about how to deal with modifications in the scenarios. In principle, new consulting processes will be required. In our study, we show how multi-criteria decision analysis can be used to analyze stakeholders' attitudes toward transition paths. Since stakeholders differ regarding their preferences and time horizons, we employ a multi-criteria decision analysis approach to identify which stakeholders will support or oppose a transition path. We provide a flexible template for analyzing stakeholder preferences toward transition paths. This flexibility comes from the fact that our multi-criteria decision aid-based approach does not involve intensive empirical work with stakeholders. Instead, it involves subjecting assumptions to robustness analysis, which can help identify options to influence stakeholders' attitudes toward transitions.
This study evaluates neuromechanical control and muscle-tendon interaction during energy storage and dissipation tasks in hypergravity. During parabolic flights, while 17 subjects performed drop jumps (DJs) and drop landings (DLs), electromyography (EMG) of the lower limb muscles was combined with in vivo fascicle dynamics of the gastrocnemius medialis, two-dimensional (2D) kinematics, and kinetics to measure and analyze changes in energy management. Comparisons were made between movement modalities executed in hypergravity (1.8 G) and gravity on ground (1 G). In 1.8 G, ankle dorsiflexion, knee joint flexion, and vertical center of mass (COM) displacement are lower in DJs than in DLs; within each movement modality, joint flexion amplitudes and COM displacement demonstrate higher values in 1.8 G than in 1 G. Concomitantly, negative peak ankle joint power, vertical ground reaction forces, and leg stiffness are similar between both movement modalities (1.8 G). In DJs, EMG activity in 1.8 G is lower during the COM deceleration phase than in 1 G, thus impairing quasi-isometric fascicle behavior. In DLs, EMG activity before and during the COM deceleration phase is higher, and fascicles are stretched less in 1.8 G than in 1 G. Compared with the situation in 1 G, highly task-specific neuromuscular activity is diminished in 1.8 G, resulting in fascicle lengthening in both movement modalities. Specifically, in DJs, a high magnitude of neuromuscular activity is impaired, resulting in altered energy storage. In contrast, in DLs, linear stiffening of the system due to higher neuromuscular activity combined with lower fascicle stretch enhances the buffering function of the tendon, and thus the capacity to safely dissipate energy.
The popularity of social media and particularly Instagram grows steadily. People use the different platforms to share pictures as well as videos and to communicate with friends. The potential of social media platforms is also being used for marketing purposes and for selling products. While for Facebook and other online social media platforms the purchase decision factors are investigated several times, Instagram stores remain mainly unattended so far. The present research work closes this gap and sheds light into decisive factors for purchasing products offered in Instagram stores. A theoretical research model, which contains selected constructs that are assumed to have a significant influence on Instagram user´s purchase intention, is developed. The hypotheses are evaluated by applying structural equation modelling on survey data containing 127 relevant participants. The results of the study reveal that ‘trust’, ‘personal recommendation’, and ‘usability’ significantly influences user’s buying intention in Instagram stores.
The complex questions of today for a world of tomorrow are characterized by their global impact. Solutions must therefore not only be sustainable in the sense of the three pillars of sustainability (economic, environmental, and social) but must also function globally. This goes hand in hand with the need for intercultural acceptance of developed services and products. To achieve this, engineers, as the problem solvers of the future, must be able to work in intercultural teams on appropriate solutions, and be sensitive to intercultural perspectives. To equip the engineers of the future with the so-called future skills, teaching concepts are needed in which students can acquire these methods and competencies in application-oriented formats. The presented course "Applying Design Thinking - Sustainability, Innovation and Interculturality" was developed to teach future skills from the competency areas Digital Key Competencies, Classical Competencies and Transformative Competencies. The CDIO Standard 3.0, in particular the standards 5, 6, 7 and 8, was used as a guideline. The course aims to prepare engineering students from different disciplines and cultures for their future work in an international environment by combining a digital teaching format with an interdisciplinary, transdisciplinary and intercultural setting for solving sustainability challenges. The innovative moment lies in the digital application of design thinking and the inclusion of intercultural as well as trans- and interdisciplinary perspectives in innovation development processes. In this paper, the concept of the course will be presented in detail and the particularities of a digital implementation of design thinking will be addressed. Subsequently, the potentials and challenges will be reflected and practical advice for integrating design thinking in engineering education will be given.
Magnetic detection structure for Lab-on-Chip applications based on the frequency mixing technique
(2018)
A magnetic frequency mixing technique with a set of miniaturized planar coils was investigated for use with a completely integrated Lab-on-Chip (LoC) pathogen sensing system. The system allows the detection and quantification of superparamagnetic beads. Additionally, in terms of magnetic nanoparticle characterization ability, the system can be used for immunoassays using the beads as markers. Analytical calculations and simulations for both excitation and pick-up coils are presented; the goal was to investigate the miniaturization of simple and cost-effective planar spiral coils. Following these calculations, a Printed Circuit Board (PCB) prototype was designed, manufactured, and tested for limit of detection, linear response, and validation of theoretical concepts. Using the magnetic frequency mixing technique, a limit of detection of 15 µg/mL of 20 nm core-sized nanoparticles was achieved without any shielding.
The movement of magnetic beads due to a magnetic field gradient is of great interest in different application fields. In this report we present a technique based on a magnetic tweezers setup to measure the velocity factor of magnetically actuated individual superparamagnetic beads in a fluidic environment. Several beads can be tracked simultaneously in order to gain and improve statistics. Furthermore we show our results for different beads with hydrodynamic diameters between 200 and 1000 nm from diverse manufacturers. These measurement data can, for example, be used to determine design parameters for a magnetic separation system, like maximum flow rate and minimum separation time, or to select suitable beads for fixed experimental requirements.
Like all preceding transformations of the manufacturing industry, the large-scale usage of production data will reshape the role of humans within the sociotechnical production ecosystem. To ensure that this transformation creates work systems in which employees are empowered, productive, healthy, and motivated, the transformation must be guided by principles of and research on human-centered work design. Specifically, measures must be taken at all levels of work design, ranging from (1) the work tasks to (2) the working conditions to (3) the organizational level and (4) the supra-organizational level. We present selected research across all four levels that showcase the opportunities and requirements that surface when striving for human-centered work design for the Internet of Production (IoP). (1) On the work task level, we illustrate the user-centered design of human-robot collaboration (HRC) and process planning in the composite industry as well as user-centered design factors for cognitive assistance systems. (2) On the working conditions level, we present a newly developed framework for the classification of HRC workplaces. (3) Moving to the organizational level, we show how corporate data can be used to facilitate best practice sharing in production networks, and we discuss the implications of the IoP for new leadership models. Finally, (4) on the supra-organizational level, we examine overarching ethical dimensions, investigating, e.g., how the new work contexts affect our understanding of responsibility and normative values such as autonomy and privacy. Overall, these interdisciplinary research perspectives highlight the importance and necessary scope of considering the human factor in the IoP.
For performing point-of-care molecular diagnostics, magnetic immunoassays constitute a promising alternative to established enzyme-linked immunosorbent assays (ELISA) because they are fast, robust and sensitive. Simultaneous detection of multiple biomolecular targets from one body fluid sample is desired. The aim of this work is to show that multiplex magnetic immunodetection based on magnetic frequency mixing by means of modular immunofiltration columns prepared for different targets is feasible. By calculations of the magnetic response signal, the required spacing between the modules was determined. Immunofiltration columns were manufactured by 3D printing and antibody immobilization was performed in a batch approach. It was shown experimentally that two different target molecules in a sample solution could be individually detected in a single assaying step with magnetic measurements of the corresponding immobilization filters. The arrangement order of the filters and of a negative control did not influence the results. Thus, a simple and reliable approach to multi-target magnetic immunodetection was demonstrated.
In modern bioanalytical methods, it is often desired to detect several targets in one sample within one measurement. Immunological methods including those that use superparamagnetic beads are an important group of techniques for these applications. The goal of this work is to investigate the feasibility of simultaneously detecting different superparamagnetic beads acting as markers using the magnetic frequency mixing technique. The frequency of the magnetic excitation field is scanned while the lower driving frequency is kept constant. Due to the particles’ nonlinear magnetization, mixing frequencies are generated. To record their amplitude and phase information, a direct digitization of the pickup-coil’s signal with subsequent Fast Fourier Transformation is performed. By synchronizing both magnetic beads using frequency scanning in magnetic frequency mixing technique magnetic fields, a stable phase information is gained. In this research, it is shown that the amplitude of the dominant mixing component is proportional to the amount of superparamagnetic beads inside a sample. Additionally, it is shown that the phase does not show this behaviour. Excitation frequency scans of different bead types were performed, showing different phases, without correlation to their diverse amplitudes. Two commercially available beads were selected and a determination of their amount in a mixture is performed as a demonstration for multiplex measurements.
Sensitive and rapid detection of cholera toxin subunit B using magnetic frequency mixing detection
(2019)
Cholera is a life-threatening disease caused by the cholera toxin (CT) as produced by some Vibrio cholerae serogroups. In this research we present a method which directly detects the toxin’s B subunit (CTB) in drinking water. For this purpose we performed a magnetic sandwich immunoassay inside a 3D immunofiltration column. We used two different commercially available antibodies to capture CTB and for binding to superparamagnetic beads. ELISA experiments were performed to select the antibody combination. The beads act as labels for the magnetic frequency mixing detection technique. We show that the limit of detection depends on the type of magnetic beads. A nonlinear Hill curve was fitted to the calibration measurements by means of a custom-written python software. We achieved a sensitive and rapid detection of CTB within a broad concentration range from 0.2 ng/ml to more
than 700 ng/ml.
It has been shown that muscle fascicle curvature increases with increasing contraction level and decreasing muscle–tendon complex length. The analyses were done with limited examination windows concerning contraction level, muscle–tendon complex length, and/or intramuscular position of ultrasound imaging. With this study we aimed to investigate the correlation between fascicle arching and contraction, muscle–tendon complex length and their associated architectural parameters in gastrocnemius muscles to develop hypotheses concerning the fundamental mechanism of fascicle curving. Twelve participants were tested in five different positions (90°/105°*, 90°/90°*, 135°/90°*, 170°/90°*, and 170°/75°*; *knee/ankle angle). They performed isometric contractions at four different contraction levels (5%, 25%, 50%, and 75% of maximum voluntary contraction) in each position. Panoramic ultrasound images of gastrocnemius muscles were collected at rest and during constant contraction. Aponeuroses and fascicles were tracked in all ultrasound images and the parameters fascicle curvature, muscle–tendon complex strain, contraction level, pennation angle, fascicle length, fascicle strain, intramuscular position, sex and age group were analyzed by linear mixed effect models. Mean fascicle curvature of the medial gastrocnemius increased with contraction level (+5 m−1 from 0% to 100%; p = 0.006). Muscle–tendon complex length had no significant impact on mean fascicle curvature. Mean pennation angle (2.2 m−1 per 10°; p < 0.001), inverse mean fascicle length (20 m−1 per cm−1; p = 0.003), and mean fascicle strain (−0.07 m−1 per +10%; p = 0.004) correlated with mean fascicle curvature. Evidence has also been found for intermuscular, intramuscular, and sex-specific intramuscular differences of fascicle curving. Pennation angle and the inverse fascicle length show the highest predictive capacities for fascicle curving. Due to the strong correlations between pennation angle and fascicle curvature and the intramuscular pattern of curving we suggest for future studies to examine correlations between fascicle curvature and intramuscular fluid pressure.
Quantitative evaluation of health management designs for fuel cell systems in transport vehicles
(2022)
Focusing on transport vehicles, mainly with regard to aviation applications, this paper presents compilation and subsequent quantitative evaluation of methods aimed at building an optimum integrated health management solution for fuel cell systems. The methods are divided into two different main types and compiled in a related scheme. Furthermore, different methods are analysed and evaluated based on parameters specific to the aviation context of this study. Finally, the most suitable method for use in fuel cell health management systems is identified and its performance and suitability is quantified.
In addition to electromobility and alternative drive systems, a focus is set on electrically driven compressors (EDC), with a high potential for increasing the efficiency of internal combustion engines (ICE) and fuel cells [01]. The primary objective is to increase the ICE torque, provided independently of the ICE speed by compressing the intake air and consequently the ICE filling level supported by the compressor. For operation independent from the ICE speed, the EDC compressor is decoupled from the turbine by using an electric compressor motor (CM) instead of the turbine. ICE performances can be increased by the use of EDC where individual compressor parameters are adapted to the respective application area [02] [03]. This task contains great challenges, increased by demands with regard to pollutant reduction while maintaining constant performance and reduced fuel consumption. The FH-Aachen is equipped with an EDC test bench which enables EDC-investigations in various configurations and operating modes. Characteristic properties of different compressors can be determined, which build the basis for a comparison methodology. Subject of this project is the development of a comparison methodology for EDC with an associated evaluation method and a defined overall evaluation method. For the application of this comparison methodology, corresponding series of measurements are carried out on the EDC test bench using an appropriate test device.
Having well-defined control strategies for fuel cells, that can efficiently detect errors and take corrective action is critically important for safety in all applications, and especially so in aviation. The algorithms not only ensure operator safety by monitoring the fuel cell and connected components, but also contribute to extending the health of the fuel cell, its durability and safe operation over its lifetime. While sensors are used to provide peripheral data surrounding the fuel cell, the internal states of the fuel cell cannot be directly measured. To overcome this restriction, Kalman Filter has been implemented as an internal state observer.
Other safety conditions are evaluated using real-time data from every connected sensor and corrective actions automatically take place to ensure safety. The algorithms discussed in this paper have been validated thorough Model-in-the-Loop (MiL) tests as well as practical validation at a dedicated test bench.