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Das Controlling hat seinen Platz in der Betriebswirtschaftslehre und damit als akademische Disziplin noch nicht gefunden, ja es ist nicht einmal allgemein geklärt, ob Controlling überhaupt eine wissenschaftliche Disziplin ist. Denn für die Anerkennung als wissenschaftliche Teildisziplin müsste es mit Kant gelingen, „das Unterscheidende, was sie mit keiner andern gemein hat, und was ihr also eigenthümlich ist“ genau zu bestimmen. Der Versuch einer derartigen „Bestimmung“ ist charakteristisch für die wissenschaftliche Beschäftigung mit „Controlling“ im deutschen Sprachraum.
Nach einem systematisierenden Überblick über bisherige Konzeptionalisierungsversuche und deren kritischer Würdigung wird aus der Erfolglosigkeit dieser Bemühungen in den letzten 50 Jahren der Schluss gezogen, dass der Versuch, „Controlling“ in Relation zur „klassischen“ Betriebswirtschaftslehre zu konzeptionalisieren, gescheitert ist. Will man nun den Versuch einer wissenschaftlichen Konzeptionalisierung nicht gänzlich aufgeben, so ist es möglicherweise sinnvoll, auf einen alternativen Referenzrahmen zurückzugreifen. Ein solcher Referenzrahmen stellt das Konzept der Privatwirtschaftslehre (PWL) dar. Dieses wird im Weiteren genutzt, um eine andere Fundierung des Controllings zu schaffen, um wiederum auf dieser Basis einen Controllingansatz zu formulieren, der die zuvor kritisierten Schwächen überwindet.
Recent research suggests that the common core of all aversive traits can be understood through the Dark Factor of Personality (D). Previously, the overlap among aversive traits has also been described as the low pole of HEXACO Honesty-Humility. Relying on longitudinal data and a range of theoretically derived outcome criteria, we test in four studies (total N > 2,500) whether and how D and low Honesty-Humility differ. Although the constructs shared around 66% of variance (meta-analytically aggregated across all studies), they longitudinally differently accounted for diverse aversive traits and showed theoretically meaningful and distinct associations to pretentiousness, distrust-related beliefs, and empathy. These results suggest that D and low Honesty-Humility are best understood as strongly overlapping, yet functionally different and nomologically distinct constructs.
River ecosystems are being threatened by rising temperatures, aridity, and salinity due to climate change and increased water abstractions. These threats also put human well-being at risk, as people and rivers are closely connected, particularly in water-scarce regions. We aimed to investigate the relationship between human well-being and biological and physico-chemical river water quality using the arid Draa River basin as a case study. Physico-chemical water measurements, biological monitoring of aquatic macroinvertebrates, and household surveys were used to assess the state of the river water, ecosystem, and human well-being, as well as the associations between them. Salinity levels exceeded maximum permissible values for drinking water in 35 % and irrigation water in 12 % of the sites. Salinity and low flow were associated with low biological quality. Human satisfaction with water quantity and quality, agriculture, the natural environment, and overall life satisfaction were low particularly in the Middle Draa, where 89% of respondents reported emotional distress due to water salinity and scarcity. Drinking and irrigation water quality was generally rated lower in areas characterized by higher levels of water salinity and scarcity. The study found positive associations between the river water quality and biological quality indices, but no significant association between these factors and human satisfaction. These findings suggest that the relationship between human satisfaction and the biological and physicochemical river water quality is complex and that a more comprehensive approach to human well-being is likely needed to establish relationships.
Micro milling is a very flexible micro cutting process widely deployed to manufacture miniaturized parts. However, size effects occur when downscaling the cutting processes. They lead to higher mechanical loads on the tools and therefore increased tool wear. Micro milling tools are usually made of cemented carbides due to their mechanical strength and fine grain structure. Technical ceramics as alternative tool materials offer very good mechanical properties as well, with grain sizes well below 1 μ m. In conventional machining, they have proven to be able to reduce tool wear. To transfer these wear improvements to the micro scale, we manufactured all-ceramic micro end mills in previous studies ( ∅ 50 and ∅ 100 μm). Tools made from zirconia (Y-TZP) showed the sharpest cutting edges, and were the best performing in micro milling trials amongst the substrates tested. However, the advantages of the ceramic substrate could not be utilized for the brass and titanium materials tested in those studies. Therefore, in this study the capabilities of all-ceramic micro end mills ( ∅ 50 μ m) in different workpiece materials (1.4404, 1.7225, 3.1325 and PMMA GS) were researched. For the two steels and the aluminum alloy, the ceramic tools did not offer an improvement over the cemented carbide tools used as reference. For the thermoplastic PMMA however, significant improvements could be achieved by utilizing the Y-TZP ceramic tools: Less tool wear, less and more stable cutting forces, and higher surface qualities.
The impact of cognitive and motivational resources on engangement with automated formative feedback
(2024)
The effectiveness of automated formative feedback highly depends on student feedback engagement that is largely determined by learners’ cognitive and motivational resources. Yet, most studies have only investigated either cognitive resources (e.g., mental effort), or motivational resources (e.g., expectancy-value-cost variables). The purpose of this study is to examine the development (indicated by time) and relationship of 1) cognitive, 2) affective, and 3) behavioral feedback engagement as a function of cognitive and motivational resources in a computer-based learning environment with automated formative feedback. Data was collected from N = 330 German B.Ed. Elementary Education students who worked four consecutive sessions on summarizing texts. Previously invested mental effort (t-1) affected situational expectancy and cost but not situational value. 1) Cognitive feedback engagement was positively associated with previous performance but neither associated with cognitive nor motivational resources. 2) Affective feedback engagement was positively associated with intrinsic value and negatively associated with situational expectancies, invested mental effort and previous performance. 3) Behavioral feedback engagement was positively associated with situational expectancies and invested mental effort. This study contributes to the understanding of student’s cognitive and motivational structures when engaging with automated formative feedback.
This survey provides the reader with an overview of numerous results on p-permu- tation modules and the closely related classes of endo-trivial, endo-permutation and endo-p- permutation modules. These classes of modules play an important role in the representation theory of finite groups. For example, they are important building blocks used to understand and parametrise several kinds of categorical equivalences between blocks of finite group alge- bras. For this reason, there has been, since the late 1990’s, much interest in classifying such modules. The aim of this manuscript is to review classical results as well as all the major recent advances in the area. The first part of this survey serves as an introduction to the topic for non-experts in modular representation theory of finite groups, outlining proof ideas of the most important results at the foundations of the theory. Simultaneously, the connections between the aforementioned classes of modules are emphasised. In this respect, results, which are dispersed in the literature, are brought together, and emphasis is put on common properties and the role played by the p-permutation modules throughout the theory. Finally, in the last part of the manuscript, lifting results from positive characteristic to characteristic zero are collected and their proofs sketched.
Postural deficits such as hyperlordosis (hollow back) or hyperkyphosis (hunchback) are relevant health issues. Diagnoses depend on the experience of the examiner and are, therefore, often subjective and prone to errors. Machine learning (ML) methods in combination with explainable artificial intelligence (XAI) tools have proven useful for providing an objective, data-based orientation. However, only a few works have considered posture parameters, leaving the potential for more human-friendly XAI interpretations still untouched. Therefore, the present work proposes an objective, data-driven ML system for medical decision support that enables especially human-friendly interpretations using counterfactual explanations (CFs). The posture data for 1151 subjects were recorded by means of stereophotogrammetry. An expert-based classification of the subjects regarding the presence of hyperlordosis or hyperkyphosis was initially performed. Using a Gaussian progress classifier, the models were trained and interpreted using CFs. The label errors were flagged and re-evaluated using confident learning. Very good classification performances for both hyperlordosis and hyperkyphosis were found, whereby the re-evaluation and correction of the test labels led to a significant improvement (MPRAUC = 0.97). A statistical evaluation showed that the CFs seemed to be plausible, in general. In the context of personalized medicine, the present study’s approach could be of importance for reducing diagnostic errors and thereby improving the individual adaptation of therapeutic measures. Likewise, it could be a basis for the development of apps for preventive posture assessment.
The objectification of acute fatigue (during isometric muscle contraction) and cumulative fatigue (due to multiple intermittent isometric muscle contractions) plays an important role in sport climbing. The data of 42 participants were used in the study. Climbing performance was operationalized using maximal climbing-specific holding time (CSHT) by performing dead hangs. The test started with an initial measurement of handgrip strength (HGS) followed by three intermittent measurements of CSHT and HGS. During the test, finger flexor muscle oxygen saturation (SmO2) was measured using a near-infrared spectroscopy wearable biosensor. Significant reductions in CSHT and HGS could be found (p < 0.001), which indicates that the consecutive maximal isometric holding introduces cumulative fatigue. The reduction in CSHT did not correlate with a reduction in HGS over multiple consecutive maximal dead hangs (p > 0.35). Furthermore, there were no significant differences in initial SmO2 level, SmO2 level at termination, SmO2 recovery, and mean negative slope of the SmO2 saturation reduction between the different measurements (p > 0.24). Significant differences were found between pre-, termination-, and recovery- (10 s after termination) SmO2 levels (p < 0.001). Therefore, monitoring acute fatigue using athletes’ termination SmO2 saturation seems promising. By contrast, the measurement of HGS and muscle oxygen metabolism seems inappropriate for monitoring cumulative fatigue during intermittent isometric climbing-specific muscle contractions.
Specific parameters of cake filtration, such as the filter cake and filter medium resistances, can be determined using the pressurized housing cell standardized in the guideline VDI 2762 by measuring the filtrate mass on a laboratory scale. For reproducible measurements and an exact detection of the filtration start, an improved test setup is presented and compared with a standard setup according to the guideline VDI 2762. On the basis of measurements without and with a particle system to be filtered, it is shown that the characteristic nonlinear course at the beginning of each filtration, which can be seen in the t/V-V diagram, is influenced by the used measuring equipment.
With the transition of fluid-capillary-based “Lab on a chip 1.0″ concepts in analytical chemistry to “Lab on a chip
2.0″ approaches relying on distinct fluid droplets (“digital microfluidics”, DMF), the need for reliable methods for
droplet actuation has increasingly come into focus. One possible approach is based on “electrowetting on
dielectric” (EWOD). This technique has the disadvantage that any possible desired later positions of the droplets
on the chip have to be defined prior to chip realization because one of the EWOD electrode layers has to be
structured accordingly. “Optoelectrowetting” (OEW) goes a step further in the sense that the later droplet positions
do not have to be known before, and none of the electrode layers has to be structured. Instead, the
electrical parameters of the layer sequence can be altered locally by an impinging (and movable) light spot.
Although some research groups have succeeded in demonstrating OEW actuation of droplets, the optimization of
the relevant parameters of the layer sequence and the droplet – at least half a dozen parameters altogether – is
tedious and not straight-forward. In this contribution, for optimization purposes, the equations governing OEW
are revisited and altered again, e.g., by numerical implementation of the experimentally well-known saturation
of the contact angle change. Additionally, a Nelder-Mead algorithm is applied to find the parameters, on which
the optimization has to focus to maximize contact angle changes and, thus, mechanical forces on the droplets.
The numerical investigation yields diverse results, e.g., the finding that the droplet’s contact area on the
dielectric layer has a strong influence on the contact angle change and the question whether the droplet is pulled
or pushed. Moreover, the interplay between frequency and amplitude of the applied rectangular alternate voltage
is important for optimization.
Das MINT-EC-Girls-Camp: Math-Talent-School richtet sich an mathematikbegeisterte Schülerinnen von MINT-EC-Schulen, die Einblicke in die Berufswelt von Mathematikerinnen und Mathematikern bekommen möchten. Die Veranstaltung veranschaulicht den Schülerinnen die steigende Relevanz angewandter mathematischer Forschungsgebiete, wie der Techno- und der Wirtschaftsmathematik. Sie soll dazu dienen, Schüler:innen die Bedeutung mathematischer Arbeitsweisen in der heutigen Berufswelt, insbesondere in Industrie und Wirtschaft, begreifbar zu machen. Die Talent-School wird organisiert von MINT-EC und dem Felix-Klein-Zentrum für Mathematik. Die fachwissenschaftliche Betreuung der Schülerinnen während dieser Talent-School wurde durch Mitarbeitende des Kompetenzzentrums für Mathematische Modellierung in MINT-Projekten in der Schule (KOMMS) der TU Kaiserslautern und des Fraunhofer ITWM umgesetzt. In diesem Report beschreiben wir die Projekte, die während der Talent-School im Oktober 2022 durchgeführt wurden.
Seit 1993 veranstaltet der Fachbereich Mathematik der TU Kaiserslautern jährlich die mathematischen Modellierungswochen. Die Veranstaltung erwuchs parallel zu der steigenden Relevanz angewandter mathematischer Forschungsgebiete, wie der Techno- und der Wirtschaftsmathematik. Sie soll dazu dienen, Schülerinnen und Schülern die Bedeutung mathematischer Arbeitsweisen in der heutigen Berufswelt, insbesondere in Industrie und Wirtschaft, begreifbar zu machen. Darüber hinaus bietet die Modellierungswoche den teilnehmenden Lehrkräften einen Einblick in die Projektarbeit mit offenen Fragestellungen im Rahmen der mathematischen Modellierung. In diesem Report beschreiben wir die Projekte, die während der Modellierungswoche im Dezember 2022 durchgeführt wurden.
We present an identification benchmark data set for a full robot movement with an KUKA KR300 R2500 ultra SE industrial robot. It is a robot with a nominal payload capacity of 300 kg, a weight of 1120 kg and a reach of 2500mm. It exhibits 12 states accounting for position and velocity for each of the 6 joints. The robot encounters backlash in all joints, pose-dependent inertia, pose-dependent gravitational loads, pose-dependent hydraulic forces, pose- and velocity dependent centripetal and Coriolis forces as well as a nonlinear friction, which is temperature dependent and therefore potentially time varying. We supply the prepared dataset for black-box identification of the forward or the inverse robot dynamics. Additional to the data for black-box modelling, we supply high-frequency raw data and videos of each experiment. A baseline and figures of merit are defined to make results compareable across different identification methods.
In recent years, the automotive industry has shifted from purely combustion engine-driven vehicles towards hybridization due to the introduction of CO2 emission legislation. Hybrid powertrains also represent an important pillar and starting point in the journey towards zero-emission and full electrification. Fulfilling the most recent emission standards requires efficient control strategies for the engine, capable of real-time operation. Model accuracy is one of the main parameters which directly influence the performance of such control strategies. Specific methodologies developed in the past, such as physically- or phenomenologically-based approaches, have already facilitated the modeling of the combustion engine. Even though these models can accurately predict emissions in steady state conditions, their performance during transient engine operation is time-consuming and still not sufficiently reliable. The major contribution of the current work is to clarify and apply the recent advancements in data-driven modeling techniques, especially in time series forecasting with feedforward neural networks (FFNNs) and long short-term memory networks (LSTMs), to address the limitations mentioned above and to compare the different approaches. The quantity and quality of data are significant challenges for data-driven modeling. This paper studies the modeling of gasoline engine emissions using FFNNs and LSTMs. The data quantity and quality requirements are studied based on a portable emission measurement system (PEMS), measuring at 1 Hz, and additional analyses on an engine test bench with a HiL setup, providing the possibility of increasing the measurement frequency with more sophisticated devices by a factor of five. Subsequently, the training and validation of the FFNNs and LSTMs are outlined, and finally, the model accuracy is discussed.
Sensing location information in indoor scenes requires a high accuracy and is a challenging task, mainly because of multipath and NLoS (non-line-of-sight) propagation. GNSS signals cannot penetrate well in indoor environment. Satellite-based navigation and positioning systems cannot therefore be used for indoor positioning.. Other technologies have been suggested for indoor usage, among them, Wi-Fi (802.11) and 5G NR (New Radio). The primary aim of this study is to discuss the advantages and drawbacks of 5G and Wi-Fi positioning techniques for indoor localization.
The fatigue life of metals manufactured via laser-based powder bed fusion (L-PBF) highly
depends on process-induced defects. In this context, not only the size and geometry of the defect, but
also the properties and the microstructure of the surrounding material volume must be considered.
In the presented work, the microstructural changes in the vicinity of a crack-initiating defect in a
fatigue specimen produced via L-PBF and made of AISI 316L were analyzed in detail. Xenon plasma
focused ion beam (Xe-FIB) technique, scanning electron microscopy (SEM), and electron backscatter
diffraction (EBSD) were used to investigate the phase distribution, local misorientations, and grain
structure, including the crystallographic orientations. These analyses revealed a fine grain structure
in the vicinity of the defect, which is arranged in accordance with the melt pool geometry. Besides
pronounced cyclic plastic deformation, a deformation-induced transformation of the initial austenitic
phase into α’-martensite was observed. The plastic deformation as well as the phase transformation
were more pronounced near the border between the defect and the surrounding material volume.
However, the extent of the plastic deformation and the deformation-induced phase transformation
varies locally in this border region. Although a beneficial effect of certain grain orientations on the
phase transformation and plastic deformability was observed, the microstructural changes found
cannot solely be explained by the respective crystallographic orientation. These changes are assumed
to further depend on the inhomogeneous distribution of the multiaxial stresses beneath the defect as
well as the grain morphology
Comparison of Premixed Fuel and Premixed Charge Operation for Propane-Diesel Dual-Fuel Combustion
(2023)
With the rising popularity of dual-fuel combustion, liquefied
petroleum gas (LPG) can be utilized in high-compression diesel
engines. Through production from biomass (biomass to liquid, BtL),
biopropane as a direct substitute for LPG can contribute to a reduction
in greenhouse gas emissions caused by combustion engines. In a
conventional dual-fuel engine, the low reactivity fuel (LRF) propane
is premixed with the intake air to form a homogeneous mixture. This
air-fuel mixture is then ignited by the high reactivity fuel (HRF) in the
form of a diesel pilot injection inside the cylinder. In the presented
work, this premixed charge operation (PCO) is compared to a method
where propane and diesel are blended directly upstream of the high-
pressure pump (premixed fuel operation, PFO) in variable mixing
ratios for different engine loads and speeds. Furthermore, the effects
of internal and external exhaust gas recirculation are investigated for
each operating mode. The results show that PCO allows higher
propane ratios of up to 75 % at low loads, while PFO enables higher
percentages of propane at medium and high loads (up to 50 %),
allowing for a “reactivity on demand” approach. In addition, PFO
shows significantly lower emissions of unburned hydrocarbons
(-98.3 %) and carbon monoxide (-94.6 %) compared to PCO while
soot emissions are reduced in both cases. The use of EGR allows
nitrogen oxide emissions to be lowered to similar levels for both
operation modes and shows benefits concerning unburned
hydrocarbon (-73.5 %) and carbon monoxide (-62.9 %) emissions in
PCO.
In micro milling, size effects such as the ratio of uncut chip thickness to cutting edge radius result to high mechanical stresses. The tools need to be able to withstand these, with as little tool wear as possible. Cemented carbides are currently the tool substrates of choice. Technical ceramics are highly wear resis- tant as well, but they are not yet used in micro milling. To utilize their potential in micro cutting pro- cesses, we previously identified Y-TZP as the best ceramic for this purpose. Compared to cemented carbide, they exhibit only marginal tool wear when micro milling PMMA. To investigate whether the 3Y-TZP characteristics influence the performance of all-ceramic micro end mills, three different substrate materials were used to manufacture tools that were tested by micro milling of PMMA. Further varied factors were the feed per tooth and the spindle speed. The initial cutting edge sharpness of the tools and the tool wear were used to quantify the results. One substrate was found to result in lower cutting edge radii and a more stable manufacturing process than the others. Also, a feed per tooth dependent wear behavior was observed.
The modified fouling index (MFI) is a crucial characteristic for assessing the fouling potential of reverse osmosis (RO) feed water. Although the MFI is widely used, the estimation time required for filtration and data evaluation is still relatively long. In this study, the relationship between the MFI and instantaneous spectroscopic extinction measurements was investigated. Since both measurements show a linear correlation with particle concentration, it was assumed that a change in the MFI can be detected by monitoring the optical density of the feed water. To prove this assumption, a test bench for a simultaneous measurement of the MFI and optical extinction was designed. Silica monospheres with sizes of 120 nm and 400 nm and mixtures of both fractions were added to purified tap water as model foulants. MFI filtration tests were performed with a standard 0.45 µm PES membrane, and a 0.1 µm PP membrane. Extinction measurements were carried out with a newly designed flow cell inside a UV–VIS spectrometer to get online information on the particle properties of the feed water, such as the particle concentration and mean particle size. The measurement results show that the extinction ratio of different light wavelengths, which should remain constant for a particulate system, independent of the number of particles, only persisted at higher particle concentrations. Nevertheless, a good correlation between extinction and MFI for different particle concentrations with restrictions towards the ratio of particle and pore size of the test membrane was found. These findings can be used for new sensory process monitoring systems, if the deficiencies can be overcome.
Heme oxygenase-1 (HO-1) is an enzyme located at the endoplasmic reticulum, which is responsible for the degradation of cellular heme into ferrous iron, carbon monoxide and biliverdin-IXa. In addition to this main function, the enzyme is involved in many other homeostatic, toxic and cancer-related mechanisms. In this review, we first summarize the importance of HO-1 in
physiology and pathophysiology with a focus on the digestive system. We then detail its structure and function, followed by a section on the regulatory mechanisms that control HO-1 expression and activity. Moreover, HO-2 as important further HO isoform is discussed, highlighting the similarities
and differences with regard to HO-1. Subsequently, we describe the direct and indirect cytoprotective functions of HO-1 and its breakdown products carbon monoxide and biliverdin-IXa, but also highlight possible pro-inflammatory effects. Finally, we address the role of HO-1 in cancer with a particular
focus on colorectal cancer. Here, relevant pathways and mechanisms are presented, through which HO-1 impacts tumor induction and tumor progression. These include oxidative stress and DNA damage, ferroptosis, cell cycle progression and apoptosis as well as migration, proliferation, and
epithelial-mesenchymal transition.
Increased bat hunting at polluted streams suggests chemical exposure rather than prey shortage
(2023)
Streams and their riparian areas are important habitats and foraging sites for bats feeding on emergent aquatic insects. Chemical pollutants entering freshwater streams from agricultural and wastewater sources have been shown to alter aquatic insect emergence, yet little is known about how this impacts insectivorous bats in riparian areas. In this study, we investigate the relationships between the presence of wastewater effluent, in-stream pesticide toxicity, the number of emergent and flying aquatic insects, and the activity and hunting behaviour of bats at 14 streams in southwestern Germany. Stream sites were located in riparian forests, sheltered from direct exposure to pollutants from agricultural and urban areas. We focused on three bat species associated with riparian areas: Myotis daubentonii, M. cf. brandtii, and Pipistrellus pipistrellus. We found that streams with higher pesticide toxicity and more frequent detection of wastewater also tended to be warmer and have higher nutrient and lower oxygen concentrations. We did not observe a reduction of insect emergence, bat activity or hunting rates in association with pesticide toxicity and wastewater detections. Instead, the activity and hunting rates of Myotis spp. were higher at more polluted sites. The observed increase in bat hunting at more polluted streams suggests that instead of reduced prey availability, chemical pollution at the levels measured in the present study could expose bats to pollutants transported from the stream by emergent aquatic insects.
Since the end of the Cold War, Germany has been considered a largely safe country. But increasing terrorism, the COVID-19 pandemic, the war in Ukraine, and national flood disasters with serious consequences have led to growing attention to civil protection issues in politics and society. Thereby the reduction of possible risks is closely linked to rescue forces being well trained and the population being adequately informed about how to behave during disasters. Thus, adult learning is central to reducing risks associated with disasters. This paper, therefore, examines what works are available from adult and continuing education research on disaster protection in Germany after the 2nd World War. The results of this first
comprehensive scoping review in this field show that pedagogical issues in disaster risk reduction are addressed by various disciplines. Most of these are practice-oriented and aim for the development of pedagogical concepts. High-quality scientific works that are empirically based or oriented towards the development of theoretical foundations, are hardly to be found. Overall, this in-depth research thus reveals a large research gap in the field of adult pedagogical research on the area of disaster education in Germany.
We present a model predictive control (MPC) algorithm for online time-optimal trajectory planning of cooperative robotic manipulators. Robotic arms sharing a common confined operational space are exposed to high interrobot collision
risks. For collision avoidance, a smooth robot geometry approximation by Bézier curves is applied, utilizing velocity constraints and tangent separating planes, enabling an efficient generation of robot trajectories in real-time. The proposed optimization algorithm is validated on an experimental setup consisting of two collaborative robotic arms performing synchronous pick-and-place tasks.
Aquatic emergent insect communities form an important link between aquatic and terrestrial
ecosystems, yet studying them is costly and time-consuming as they are usually
diverse and superabundant. Metabarcoding is a valuable tool to investigate arthropod
community compositions, however high-throughput applications, such as for biomonitoring,
require cost-effective and user-friendly procedures. To investigate if the time-consuming
and labour-intensive DNA extraction step can be omitted in metabarcoding, we
studied the difference in detection rates and individual read abundance using standard
DNA extraction versus direct PCR protocols. Metabarcoding with and without DNA extraction
was performed with artificially created communities of known composition as
well as on natural communities both of the dipteran family Chironomidae to compare
detection rates, individual read abundances and presence-absence community composition.
We found that the novel approach of direct PCR metabarcoding presented here
did not alter detection rates and had a minor effect on individual read abundances in
artificially created communities. Furthermore, presence-absence community compositions
of natural chironomid communities were highly comparable using both approaches.
In conclusion, we showed that direct PCR protocols can be applied in chironomid
metabarcoding approaches, with possible application for a wider range of arthropod
taxa, enabling us to study communities more efficiently in the future.
The Arctic is undergoing strong environmental changes, affecting species and
whole biological communities. To assess the impact on these communities,
including their composition and functions, we need more information on their
current distribution and biology. In the High-Arctic tundra, dung from animals,
such as muskoxen (Ovibos moschatus), is a relatively understudied microhabitat
that may be attractive for organisms like dung-feeding insects as well as gastrointestinal
parasites. Using a DNA barcoding approach, we examined muskox
droppings from two Greenlandic regions for dung-dwelling invertebrates. In
15% of all samples, we found the DNA of insect species in the orders Diptera
and Lepidoptera. The saprophagous Diptera colonized dung differently in west
versus north-east Greenland and summer versus winter. In addition, we found
muskox dung harbouring endoparasitic nematodes in samples from both
regions. However, we could not find traces of saprophagous arthropods, such as
collembolans and mites, from the soil sphere. Our pilot study sheds a first light on the invertebrates living in this neglected Arctic microhabitat.
This pilot study aimed to investigate the use of sensorimotor insoles in pain reduction, different orthopedic indications, and the wearing duration effects on the development of pain. Three hundred and forty patients were asked about their pain perception using a visual analog scale (VAS) in a pre–post analysis. Three main intervention durations were defined: VAS_post: up to 3 months, 3 to 6 months, and more than 6 months. The results show significant differences for the within-subject factor “time of measurement”, as well as for the between-subject factor indication (p < 0.001) and worn duration (p < 0.001). No interaction was found between indication and time of measurements (model A) or between worn duration and time of measurements (model B). The results of this pilot study must be cautiously and critically interpreted, but may support the hypothesis that sensorimotor insoles could be a helpful tool for subjective pain reduction. The missing control group and the lack of confounding variables such as methodological weaknesses, natural healing processes, and complementary therapies must be taken into account. Based on these experiences and findings, a RCT and systematic review will follow.
Optimizing a manufacturing company's in-house energy demand amidst fluctuating electricity prices and uncertainties in renewable energy supply as well as volatile manufacturing planning situations is a challenging task. To tackle this issue, a novel approach is developed for scheduling the energy supply in manufacturing systems with the objective of reducing energy costs. The approach employs Quantum Annealing to determine the optimal mix of in-house generation, purchased electricity, and energy storage. The effectiveness and scalability of the approach are demonstrated through the validation using two simplified use cases, showcasing its potential in solving complex energy supply optimization problems.
Several studies now document the disproportionate distribution of environmental pollution across different groups, but many are based on aggregated data or subjective pollution measures. In this study, we describe the air quality disadvantage of migrants in Germany using objective pollution data linked to nationally representative individual-level survey data. We intersect 1 × 1 km2 grid geo-references from the German General Social Survey (ALLBUS) 2014, 2016, and 2018 with 2 × 2 km2 estimates of annually averaged air pollution by the German Environment Agency for nitrogen dioxide, ozone, and particulate matter. Respondents with a migration background are exposed to higher levels of nitrogen dioxide and particulate matter than people of German descent. Urbanity of residence partly explains these differences, up to 81 per cent for particulate matter and about 30 per cent for other pollutants. A larger proportion of immigrants live in larger cities, which are more prone to high levels of air pollution. This is especially true for second-generation migrants. Income differences, on the other hand, do not explain the migrant disadvantage. In city fixed effects models, the patterns for migration background point unambiguously in the direction of environmental disadvantage for all pollutants except ozone. However, the within-municipality associations are weak.
Physical vapor deposition (PVD) coatings are vital for enhancing wear resistance. However this technology faces challenges when coating inaccessible surfaces due to its line-of-sight characteristic. A potential remedy is utilizing triboactive CrAlMoN coatings. These form a tribofilm in the contact zone when applied to one contact partner along with a suitable lubricant. This tribofilm can subsequently safeguard inaccessible yet tribologically stressed surfaces. One of the main applications for this method is roller chain drives, whose longevity depends on the joint wear and the resulting chain elongation. Large-scale pin coatings have proven effective in curbing wear and prolonging chain life. However, the inaccessibility of bushes complicates standard PVD coating procedures. Triboactive coatings offer the possibility of forming transfer layers on the bushes, thereby enhancing friction reduction and wear protection. Experimental material studies for chain drives can be cost-intensive due to complexity and numerous components. This article demonstrates that CrAlN and CrAlMoN coatings in combination with greases with the additives phosphorus and sulfur can reduce friction and wear in chain joints. Furthermore, it is shown that a reasonable selection of tribometer testing can significantly reduce costs. Comparing the results of tests on a pin-on-disk tribometer and component tests show that model tests cannot completely replace component tests. But the combination offers an efficient way to optimize test matrices. Triboactive coatings like CrAlMoN hold promise for addressing the challenge of inaccessible surfaces. Reasonable tribometer test selection can help mitigate the costs of experimental studies, making these coatings a more practical
solution.
In the field of liquid filtration, the realization of gas throughput-free cake filtration has been investigated for a long time. Cake filtration without gas throughput would lead to energy savings in general and would reduce the mechanically achievable residual moisture in filter cakes in particular. The reason why gas throughput-free filtration could not be realized with fabrics so far is that the achievable pore sizes are not small enough, and that the associated capillary pressure is too low for gas throughput-free filtration. Microporous membranes can prevent gas flow through open pores and cracks in the filter cake at a standard differential pressure for cake filtration of 0.8 bar due to their smaller pore size. Since large-scale implementation with membranes was not yet successful due to their inadequate mechanical strength, this work focuses on the development and testing of a novel composite material. It combines the advantages of gas throughput-free filtration using membranes with the mechanical stability of fabrics. For the production of the composites, a paste dot coating with adhesive, which is a common method in the textile industry, was used. Based on filtration experiments, delamination and tensile tests, as well as CT analysis, it is shown that this method is suitable for the production of composite filter materials for gas throughput-free cake filtration.
Spreading dynamics on lithium niobate: An example of an intrinsically charged ferroelectric surface
(2023)
Droplet wetting and manipulation are essential for the efficient functioning of many applications, ranging from microfluidic applications to electronic devices, agriculture, medical diagnosis, etc. As a means of manipulating droplet wetting, the effect of applying an external voltage or surface charge has been extensively exploited and is known as electrowetting. However, there also exist many materials which bear a quasi-permanent surface charge, like electrets, which are widely employed in sensors or energy storage. In addition, other materials in nature can acquire surface charge by the triboelectric effect, like human hair, natural rubber, and polymers. Nevertheless, there do not exist any studies on spreading on this class of charged surfaces. In our work, we for the first time investigate spreading dynamics on lithium niobate (LiNbO3) as an example of a ferroelectric material with strong instantaneous polarization (0.7C/m2). We find a spreading behavior that significantly differs from classic surfaces. Spreading times can be significantly enlarged compared to standard surfaces, up to hundreds of seconds. Furthermore, the classic Tanner’s law does not describe the spreading dynamics. Instead, the evolution of the droplet radius is dominated by an exponential law. Contact angles and spreading dynamics are also polarization-dependent. They are also influenced by adsorption layers, such as they are left behind by cleaning. Overall, all results indicate that adsorption layers play a significant role in the wetting dynamics of lithium niobate and possibly other charged materials, where such processes are very pronounced. Possible mechanisms are discussed. Our findings are essential for the understanding of wetting on charged surfaces like ferroelectric materials in general. The knowledge of surface charge-based wettability difference, surface charge specific adsorption and its impact on wettability can be utilized in applications like, printing, microfluidics, triboelectric nanogenerators, and to develop biocompatible components for tissue engineering.
The driving process involves many layers of planning and navigation, in order to enable tractable solutions for the otherwise highly complex problem of autonomous driving. One such layer involves an inherent discrete layer of decision-making corresponding to tactical maneuvers. Inspired by this, the focus of this work is predicting high-level maneuvers for the ego-vehicle. As maneuver prediction is fundamentally feedback-structured, it requires modeling techniques that take into consideration the interaction awareness of the traffic agents involved. This work
addresses this challenge by modeling the traffic scenario as an interaction graph and proposing three deep learning architectures for interaction-aware tactical maneuver prediction of the ego-vehicle. These architectures are based on graph neural networks (GNNs) for extracting spatial features among traffic agents and recurrent neural networks (RNNs) for extracting dynamic motion patterns of surrounding agents. These proposed architectures have been trained and evaluated using BLVD dataset. Moreover, this dataset is expanded using data augmentation, data oversampling and data undersampling approaches, to strengthen model's resilience and enhance the learning process. Lastly, we compare proposed learning architectures for ego-vehicle maneuver prediction in various driving circumstances with various numbers of surrounding traffic agents in order to effectively verify the proposed architectures.
The amyloid precursor protein (APP) is a key molecular component of Alzheimer’s disease (AD) pathogenesis. Proteolytic APP processing generates various cleavage products, including extracellular amyloid beta (Aβ) and the cytoplasmic APP intracellular domain (AICD). Although the role of AICD in the activation of kinase signaling pathways is well established in the context
of full-length APP, little is known about intracellular effects of the AICD fragment, particularly within discrete neuronal compartments. Deficits in fast axonal transport (FAT) and axonopathy documented in AD-affected neurons prompted us to evaluate potential axon-autonomous effects of the AICD fragment for the first time. Vesicle motility assays using the isolated squid axoplasm
preparation revealed inhibition of FAT by AICD. Biochemical experiments linked this effect to aberrant activation of selected axonal kinases and heightened phosphorylation of the anterograde motor protein conventional kinesin, consistent with precedents showing phosphorylation-dependent regulation of motors proteins powering FAT. Pharmacological inhibitors of these kinases alleviated the AICD inhibitory effect on FAT. Deletion experiments indicated this effect requires a sequence encompassing the NPTY motif in AICD and interacting axonal proteins containing a phosphotyrosinebinding domain. Collectively, these results provide a proof of principle for axon-specific effects of AICD, further suggesting a potential mechanistic framework linking alterations in APP processing, FAT deficits, and axonal pathology in AD.
The measurement and assessment of indoor air quality in terms of respirable particulate constituents is relevant, especially in light of the COVID-19 pandemic and associated infection events. To analyze indoor infectious potential and to develop customized hygiene concepts, the measurement
monitoring of the anthropogenic aerosol spreading is necessary. For indoor aerosol measurements
usually standard lab equipment is used. However, these devices are time-consuming, expensive and unwieldy. The idea is to replace this standard laboratory equipment with low-cost sensors widely used for monitoring fine dust (particulate matter—PM). Due to the low acquisition costs, many sensors can be used to determine the aerosol load, even in large rooms. Thus, the aim of this work
is to verify the measurement capability of low-cost sensors. For this purpose, two different models of low-cost sensors are compared with established laboratory measuring instruments. The study
was performed with artificially prepared NaCl aerosols with a well-defined size and morphology. In addition, the influence of the relative humidity, which can vary significantly indoors, on the measurement capability of the low-cost sensors is investigated. For this purpose, a heating stage was
developed and tested. The results show a discrepancy in measurement capability between low-cost sensors and laboratory measuring instruments. This difference can be attributed to the partially different measuring method, as well as the different measuring particle size ranges. The determined measurement accuracy is nevertheless good, considering the compactness and the acquisition price of the low-cost sensors.
In this work, we investigate and compare the condensation behavior of hydrophilic, hydrophobic, and biphilic microgrooved silicon samples etched by reactive ion etching. The microgrooves were 25 mm long and 17−19 μm deep with different
topologies depending on the etching process. Anisotropically etched samples had 30 μm wide rectangular microgrooves and silicon ridges between them. They were either left hydrophilic or covered with a hydrophobic fluorocarbon or photoresist layer.
Anisotropically etched samples consisted of 48 μm wide semicircular shaped microgrooves, 12 μm wide silicon ridges between them, and a 30 μm wide photoresist stripe centered on the ridges. The lateral dimensions were chosen to be much smaller than the capillary length of water to support drainage of droplets by coalescence rather than droplet sliding. Furthermore, to achieve a low thermal resistance of the periodic surface structure consisting of water-filled grooves and silicon ridges, the trench depth was also kept small. The dripped-off total amount of condensate (AoC) was measured for each sample for 12 h under the same boundary
conditions (chamber temperature 30 °C, cooling temperature 6 °C, and relative humidity 60%). The maximum increase in AoC of 15.9% (9.6%) against the hydrophilic (hydrophobic) reference sample was obtained for the biphilic samples. In order to elucidate their unique condensation behavior, in situ optical imaging was performed at normal incidence. It shows that the drainage of droplets from the stripe’s surface into the microgrooves as well as occasional droplet sliding events are the dominant processes to clear the surface. To rationalize this behavior, the Hough Circle Transform algorithm was implemented for image processing to receive
additional information about the transient droplet size and number distribution. Postprocessing of these data allows calculation
Monitoring of patient-reported outcomes and providing therapists with progress feedback has been shown to be beneficial for treatment outcomes (e.g., by preventing therapy failures). Despite recent advances in monitoring and feedback research, little is known about why some therapists benefit from feedback more than others. Addressing this issue, the present article uses the basic science literature on belief updating to propose a theoretical model for these between-therapist differences. In doing so, we provide a novel framework that allows testable hypotheses about when and how feedback on therapy progress is likely to improve treatment outcomes. In particular, we argue that the integration of feedback and its effect on therapists’ behavior depends on the weight therapists assign to their prior beliefs regarding treatment progress relative to the weight of the feedback received. We conclude by outlining some directions for future research on the underpinnings of this model, and point to some implications for the training of therapists and provision of feedback.
Several governmental organizations all over the world aim for algorithmic accountability of artificial intelligence systems. However, there are few specific proposals on how exactly to achieve it. This article provides an extensive overview of possible transparency and inspectability mechanisms that contribute to accountability for the technical components of an algorithmic decision-making system. Following the different phases of a generic software development process, we identify and discuss several such mechanisms. For each of them, we give an estimate of the cost with respect to time and money that might be associated with that measure.
CFD-DEM Simulation of Superquadric Cylindrical Particles in a Spouted Bed and a Rotor Granulator
(2023)
The fluidization behavior of cylindrical particles in a spouted bed was first investigated experimentally using a camera setup. The obtained average spouted bed height was used to evaluate the accuracy of different drag models in CFD-DEM simulations with the superquadric approach to model the particle shape. The drag model according to Sanjeevi et al. showed the best agreement. With this model, cylindrical particles were simulated in a rotor granulator and the particle dynamics were compared with the fluidization of volume equivalent spherical particles.
The development of algorithmic differentiation (AD) tools focuses mostly on handling floating point types in the target language. Taping optimizations in these tools mostly focus on specific operations like matrix vector products. Aggregated types like std::complex are usually handled by specifying the AD type as a template argument. This approach provides exact results, but prevents the use of expression templates. If AD tools are extended and specialized such that aggregated types can be added to the expression framework, then this will result in reduced memory utilization and improve the timing for applications where aggregated types such as complex number or matrix vector operations are used. Such an integration requires a reformulation of the stored data per expression and a rework of the tape evaluation process. We will demonstrate the overheads on a synthetic benchmark and show the improvement when aggregated types are handled properly by the expression framework of the AD tool.
In the last decades, the phase field method has drawn much attention for its application in fracture mechanics because it offers a simple unified framework for crack propagation. The core idea of phase field models for fracture is to introduce a continuous scalar field representing the discontinuous crack. Recently, a phase field model for fatigue has been proposed along this path. The fatigue failure differs from the other fracture scenarios since cracks only occur after a considerable number of load cycles. As fracturing happens, changes of the material microstructure are involved, which causes the evolution of the structural configuration. Thus, a new mathematical description not based on traditional spatial coordinates but the material manifold is desired, which will serve as an elegant analysis tool to understand the energetic forces for crack propagation. Configurational forces are a suitable choice for this purpose, as they describe the energetic driving forces associated with phenomena changing the material itself. In this work, we present a phase field model for fatigue. Furthermore, the phase field fatigue model is analyzed within the concept of configurational forces, which provides a straightforward way to understand the phase field simulations of fatigue fracture.
Development of a simple substitute model to describe the normal force of fluids in narrow gaps
(2023)
Fluids in narrow gaps are employed frequently in many applications. The motivation for their use is diverse and ranges from hydrodynamic lubrication in plain bearings to the transport of hard particles into the working gap for the purpose of machining workpiece surfaces in lapping processes. Depending on the focus of the analysis, it may be useful to investigate the entire pressure field or to calculate only individual quantities. For example, in sophisticated simulations it may be of interest to know the resulting force of a fluid as a function of the external system state in order to describe its damping characteristics. Especially for the simulation of flows in narrow gaps, the Reynolds equation is a convenient choice, which, in contrast to the more general Navier-Stokes equations, can lead to considerable savings in computational time because no three-dimensional discretization is required, but only a two-dimensional discretization. However, if not a highly detailed pressure field is of interest, but only simple relations such as the resulting force as a function of distance and velocity, and if this relation to be evaluated many times for different parameter combinations over a wide range of values, the use of a robust substitute model is a good choice. This article deals with the creation of such a substitute model based on the Reynolds equation taking cavitation into account.
Tracking waterborne microplastic (MP) in urban areas is a challenging task because of the various sources and transport pathways involved. Since MP occurs in low concentrations in most wastewater and stormwater streams, large sample volumes need to be captured, prepared, and carefully analyzed. The recent research in urban areas focused mainly on MP emissions at wastewater treatment plants (WWTPs), as obvious entry points into receiving waters. However, important transport pathways under wet-weather conditions are yet not been investigated thoroughly. In addition, the lack of comprehensive and comparable sampling strategies complicated the attempts for a deeper understanding of occurrence and sources. The goal of this paper is to (i) introduce and describe sampling strategies for MP at different locations in a municipal catchment area under dry and wet-weather conditions, (ii) quantify MP emissions from the entire catchment and two other smaller ones within the bigger catchment, and (iii) compare the emissions under dry and wet-weather conditions. WWTP has a high removal rate of MP (>96%), with an estimated emission rate of 189 kg/a or 0.94 g/[population equivalents (PEQ · a)], and polyethylene (PE) as the most abundant MP. The specific dry-weather emissions at a subcatchment were ≈30 g/(PEQ · a) higher than in the influent of WWTP with 23 g/(PEQ · a). Specific wet-weather emissions from large sub-catchment with higher traffic and population densities were 1952 g/(ha · a) higher than the emissions from smaller catchment (796 g/[ha · a]) with less population and traffic. The results suggest that wet-weather transport pathways are likely responsible for 2–4 times more MP emissions into receiving waters compared to dry-weather ones due to tire abrasion entered from streets through gullies. However, more investigations of wet-weather MP need to be carried out considering additional catchment attributes and storm event characteristics.
Model-based prediction is becoming increasingly important to meet the ever-increasing demands on manufacturing. In grinding, the prediction of the process forces and the generated surface by physical models are particularly important.Since cooling lubricants are almost always used on an industrial scale, the grinding model, developed at our institut, must be extended to include this component. Therefore, in order to implement cooling lubricants into the FEM-based model, it is first necessary to investigate the behaviors and effects of cooling lubricants in real experiments. Various influencing factors such as the scratching speed of individual abrasive grains in interaction with cooling lubricants need to be investigated. However, the existing physical grinding model is not limited exclusively to the prediction of the resulting forces. It is also supposed to be able to qualitatively predict the expected resulting surface of the workpiece. Hence, this paper will focus on the topographic characteristics that can occur in the scratch test due to different cooling lubricants and scratching speeds.Based on real experiments on a test rig for such scratch tests, it has been shown that different scratch speeds have a negligible influence on the topographical nature and expression of a scratch. In contrast, however, there is a direct influence of cooling lubricants on the topographic properties. This effect is additionally influenced by the viscosity of the cooling lubricant used.
In selective laser melting (SLM), a powdered material is locally melted by a laser and, after cooling, forms a coherent solid structure that enables the production of complex geometries with various materials. The process involves extreme heating and cooling rates and, thus, large temperature gradients, which lead to anisotropic material properties on the macroscopic scale and, in the worst case, reduced mechanical properties. In order to reliably predict the final mechanical component properties, simulations can be performed at different time and length scales. Enormous computational resources are often required to perform such simulations. In order to transform these simulations into suitable surrogate models, the generated data must be compressed and evaluated in a suitable way. This paper shows first preliminary work and a possible new data description of such simulations.
Based on conservation of resources theory, this paper examines the mediating mechanisms in the relationship between digital affordances and employee corporate entrepreneurship participation likelihood. Findings from an experimental study with 207 employees show a statistically significant and positive indirect effect of digital affordances on employee corporate entrepreneurship participation likelihood through employee-perceived information technology support for innovation and a statistically significant and—contrary to our expectations—positive indirect effect through employee-perceived work overload. Results are corroborated by insights from in-depth interviews with senior managers. They provide support for digital affordances as action potentials that are associated with resource gains that in turn foster employee corporate entrepreneurship participation likelihood.
The great flexibility of direct laser writing (DLW) arises from the possibility to fabricate precise three-dimensional structures on very small scales as well as the broad range of applicable materials. However, there is still a vast number of promising materials, which are currently inaccessible requiring the continuous development of novel photoresists. Herein, a new bio-sourced resist is reported that uses the monomeric unit of chitin, N-acetyl-D-glucosamine, paving the way from existing hydrogel resists based on animal carbohydrates to a new class of non-hydrogel ones. In addition, it is shown that the combined use of two photoinitiators is advantageous over the use of a single one. In this approach, the first photoinitiator is a good two-photon absorber at the applied wavelength, while the second photoinitiator exhibits poor two-photon absorbtion abilities, but is better suited for cross-linking of the monomer. The first photoinitiator absorbs the light acting as a sensitizer and transfers the energy to the second initiator, which subsequently forms a radical and initializes the polymerization. This sensitization effect enables a new route to utilize reactive photointiators with a small two-photon absorption cross section for DLW without changing their chemical structure.
Scaled boundary isogeometric analysis (SB-IGA) describes the computational domain by proper boundary NURBS together with a well-defined scaling center; see [5]. More precisely, we consider star convex domains whose domain boundaries correspond to a sequence of NURBS curves and the interior is determined by a scaling of the boundary segments with respect to a chosen scaling center. However, providing a decomposition into star shaped blocks one can utilize SB-IGA also for more general shapes. Even though several geometries can be described by a single patch, in applications frequently there appear multipatch structures. Whereas a C0 continuous patch coupling can be achieved relatively easily, the situation becomes more complicated if higher regularity is required. Consequently, a suitable coupling method is inevitably needed for analyses that require global C1 continuity.In this contribution we apply the concept of analysis-suitable G1 parametrizations [2] to the framework of SB-IGA for the C1 coupling of planar domains with a special consideration of the scaling center. We obtain globally C1 regular basis functions and this enables us to handle problems such as the Kirchhoff-Love plate and shell, where smooth coupling is an issue. Furthermore, the boundary representation within SB-IGA makes the method suitable for the concept of trimming. In particular, we see the possibility to extend the coupling procedure to study trimmed plates and shells.The approach was implemented using the GeoPDEs package [1] and its performance was tested on several numerical examples. Finally, we discuss the advantages and disadvantages of the proposed method and outline future perspectives.
Surface wetting can be simulated using a phase field approach which describes the continuous liquid-gas transition with the help of an order parameter. In this publication, wetting of non-planar surfaces is investigated based on a phase field model by Diewald et al. [1, 2]. Different scenarios of droplets on rough surfaces are simulated. The static equilibrium for those scenarios is calculated using an Allen-Cahn evolution equation. The influence of the surface morphology on the resulting contact angle is investigated while the width of the phase transition from liquid to gas is varied as a model parameter.
Jet loop reactors are standard multiphase reactors used in chemical, biological and environmental processes. The strong liquid jet provided by a nozzle enforces both internal circulation of liquid and gas as well as entrainment and dispersion of the gas phase. We present a one-dimensional compartment model based on a momentum balance that describes the internal circulation of gas and liquid phase in the jet loop reactor. This model considers the influence of local variations of the gas volume fraction on the internal circulation. These local variations can be caused by coalescence of gas bubbles, additional gas-feeding points and gas consumption or production. In this work, we applied the model to study the influence of a gas-consuming reaction on the internal circulation. In a comprehensive sensitivity analysis, the interaction of different parameters such as rate of reaction, power input through the nozzle, gas holdup, reactor geometry, and circulation rate were investigated. The results show that gas consumption can have a significant impact on internal circulation. Industrially relevant operating conditions have even been found where the internal circulation comes to a complete standstill.
Caregivers typically use a simplified mode of the language – child-directed speech (CDS) – when addressing young children. In this study, we investigate the use of complex morphological structures with a word class change within a single word in Inuktitut CDS. Inuktitut is a polysynthetic agglutinative language of the Inuit–Yupik–Unangan language family spoken in arctic Quebec, which allows more than 10 morphemes per word and in which the meaning of an entire sentence can be expressed in one word. Clearly, such a complex morphological system presents special challenges for young children, which raises the question of whether caregivers shape their CDS in ways that facilitate acquisition. Using the data from mothers addressing eight Inuktitut-speaking children aged 0;11 to 3;6, we investigated whether the frequency and complexity of polysynthetic structures in CDS are dependent on the stage of the children’s linguistic development. The results demonstrate that the number and morphological complexity of the structures with a word class change increased as the children developed linguistically. The variety of nominalizers and verbalizers – the key components of such structures – also increased through the stages and were used in variation sets, which help children acquire morphological items by providing examples of use of the same morpheme in morphologically contrasting environments. These results show the presence of morphological simplification in Inuktitut CDS and demonstrate that such simplification is fine-tuned, i.e., that mothers are sensitive to their children’s level of linguistic development.
Work on the use of cyclic peptides or pseudopeptides as synthetic receptors started even before the field of supramolecular chemistry was firmly established. Research initially focused on the development of synthetic ionophores and involved the use of macrocycles with a repeating sequence of subunits along the ring to facilitate the correlation between structure, conformation, and binding properties. Later, nonnatural amino acids as building blocks were also considered. With growing research in this area, cyclopeptides and related macrocycles developed into an important and structurally diverse receptor family. This review provides an overview of these developments, starting from the early years. The presented systems are classified according to characteristic structural elements present along the ring. Wherever possible, structural aspects are correlated with binding properties to illustrate how natural or nonnatural amino acids affect binding properties.
Hordatines are a characteristic class of secondary metabolites found in barley which have
been reported to be present in barley malt, beer and, recently, brewer ́s spent grain (BSG). However,
little is known about their biological activities such as antioxidative effects in beer or antifungal
activity as their main task within the plants. We conducted an in vitro investigation of the activity
of hordatines isolated from BSG towards enzymes of glucose metabolism. Hordatine-rich fractions
from BSG were prepared by solid-liquid extraction (SLE) with 60% acetone followed by purification
and fractionation. The fractions were characterised and investigated for their in vitro inhibitory
potential on α-glucosidase and glycogen phosphorylase α (GPα). Both enzymes are relevant within
the human glucose metabolism regarding the digestion of carbohydrates as well as the liberation of
glucose from the liver. In total, 10 hordatine-rich fractions varying in the composition of different
hordatines were separated and analysed by mass spectrometry. Hordatine A, B and C, as well as
hydroxylated aglycons and many glycosides, were detected in the fractions. The total hordatine
content was analysed by HPLC-DAD using a semi-quantitative approach and ranged from 60.7 ± 3.1
to 259.6 ± 6.1 μg p-coumaric acid equivalents/mg fraction. Regarding the biological activity of
fractions, no inhibitory effect on GPα was observed, whereas an inhibitory effect on α-glucosidase
was detected (IC50 values: 77.5 ± 6.5–194.1 ± 2.6 μg/mL). Overall, the results confirmed that
hordatines are present in BSG in relatively high amounts and provided evidence that they are potent
inhibitors of α-glucosidase. Further research is needed to confirm these results and identify the active
hordatine structure.
We present an identification benchmark data set for a full robot movement with an KUKA KR300 R2500 ultra SE industrial robot. It is a robot with a nominal payload capacity of 300 kg, a weight of 1120 kg and a reach of 2500mm. It exhibits 12 states accounting for position and velocity for each of the 6 joints. The robot encounters backlash in all joints, pose-dependent inertia, pose-dependent gravitational loads, pose-dependent hydraulic forces, pose- and velocity dependent centripetal and Coriolis forces as well as a nonlinear friction, which is temperature dependent and therefore potentially time varying. We supply the prepared dataset for black-box identification of the forward or the inverse robot dynamics. Additional to the data for black-box modelling, we supply high-frequency raw data and videos of each experiment. A baseline and figures of merit are defined to make results compareable across different identification methods.
Understanding the mechanisms and controlling
the possibilities of surface nanostructuring is of crucial interest
for both fundamental science and application perspectives.
Here, we report a direct experimental observation
of laser-induced periodic surface structures (LIPSS) formed
near a predesigned gold step edge following single-pulse
femtosecond laser irradiation. Simulation results based on a
hybrid atomistic-continuum model fully support the experimental
observations. We experimentally detect nanosized
surface features with a periodicity of ∼300 nm and heights of
a few tens of nanometers.We identify two key components of
single-pulse LIPSS formation: excitation of surface plasmon
polaritons and material reorganization. Our results lay a
solid foundation toward simple and efficient usage of light
for innovative material processing technologies.
The mapping of a virtual network service onto a physical network infrastructure is a challenging task due to the joint allocation of virtual resources across nodes and links, the diverse technical requirements of end-users, the coordination between multiple host domains, and others. This issue is exacerbated further by the extension of virtualization to the next-generation radio access network (NG-RAN) architecture and the provisioning of radio access network (RAN) slicing. To that end, this article focuses on the mapping problem of the virtual network functions (VNFs), as well as their internal and external virtual links (VLs), of a RAN slice subnet onto intelligent points of presence (I-PoPs) and transport networks in the NG-RAN architecture. In this context, in contrast to the majority of the state-of-the-art proposals, which frequently fail to achieve performance objectives and neglect resource allocation constraints, this article introduces automation and intelligence at an architectural level to map VNFs and VLs onto their corresponding physical nodes and links, with the goal of achieving superior efficiency in virtual resource utilization while granting the performance of a RAN slice subnet. Benefiting from a top-down approach, the key contributions of this article are: (i) to extend the architectural framework of network slicing towards the NG-RAN architecture and provide a comprehensive overview and critical analysis of the components and functionalities of a RAN slice subnet; (ii) to integrate the Experiential Network Intelligence (ENI) framework into a joint architecture of the network functions virtualization–management and orchestration (NFV–MANO), Third Generation Partnership Project-network slicing management system (3GPP-NSMS), and I-PoPs in order to render automation and intelligence to the management and orchestration aspects of a RAN slice subnet in the NG-RAN architecture; and (iii) to propose a learning-assisted architectural solution for mapping the VNFs, as well as their internal and external VLs, of a RAN slice subnet onto the underlying I-PoPs and transport networks.
Load modeling is one of the crucial tasks for improving smart grids’ energy efficiency. Among many alternatives, machine learning-based load models have become popular in applications and have shown outstanding performance in recent years. The performance of these models highly relies on data quality and quantity available for training. However, gathering a sufficient amount of high-quality data is time-consuming and extremely expensive. In the last decade, Generative Adversarial Networks (GANs) have demonstrated their potential to solve the data shortage problem by generating synthetic data by learning from recorded/empirical data. Educated synthetic datasets can reduce prediction error of electricity consumption when combined with empirical data. Further, they can be used to enhance risk management calculations. Therefore, we propose RCGAN, TimeGAN, CWGAN, and RCWGAN which take individual electricity consumption data as input to provide synthetic data in this study. Our work focuses on one dimensional times series, and numerical experiments on an empirical dataset show that GANs are indeed able to generate synthetic data with realistic appearance.
Longwave radiative heat transfer is a key determinant of energy consumption in buildings
and view factor calculations are therefore required for the detailed simulation of heat transfer
between buildings and their environment as well as for heat exchange within rooms. Typically,
these calculations are either derived through analytical means or performed as a part of the simulation
process. This paper describes the methodology for employing RADIANCE, a command-line
open-source raytracing software, for performing view factor calculations. Since it was introduced
in the late-1980s, RADIANCE has been almost exclusively employed as the back-end engine for
lighting simulations. We discuss the theoretical basis for calculating view factors through Monte
Carlo calculations with RADIANCE and propose a corresponding workflow. The results generated
through RADIANCE are validated by comparing them with analytical solutions. The fundamental
methodology proposed in this paper can be scaled up to calculate view factors for more complex,
practical scenarios. Furthermore, the portability, multi-processing functionality and cross-platform
compatibility offered by RADIANCE can also be employed in the calculation of view factors.
The fluid dynamic (flow rates) and hydrodynamic behavior (local droplet size distributions and local holdup) of a continuous DN300 pump-mixer were investigated using water as the continuous phase and paraffin oil as the dispersed phase. The influence of the impeller speed (375 to 425 rpm), the feed phase ratio (10 to 30 volume percent), and the total flow rate (0.5 to 2.3 L/min) were investigated by measuring the pumping height, local holdup of the disperse phase, and the droplet size distribution (DSD). The latter one was measured at three different vessel positions using an image-based telecentric shadowgraphic technique. The droplet diameters were extracted from the acquired images using a neural network. The Sauter mean diameters were calculated from the DSD and correlated with an extended model based on Doulah (1975), considering the impeller speed, the feed phase ratio, and additionally the flow rate. The new correlation can describe an extensive database containing 155 experiments of the fluid and hydrodynamic within a 15 % error range
Ultrasonic processes such as ultrasonic welding or ultrasonic fatigue testing use power
ultrasound to stimulate materials with amplitudes in the range of 1–100 µm. The ultrasonic welding
process is sensitive to any changes in the system or even the environment that may result in lower
joint quality. The welding tools, so called sonotrodes, have to be accurately designed to endure high
mechanical and thermal loads while inducing a sufficient amount of welding energy into the joining
zone by oscillation with the Eigenfrequency of the whole system. Such sonotrodes are often made of
thermally treated metals where the heat treatment is accompanied by microstructural changes. During
ultrasonic stimulation, the material may further change its properties and microstructure due to cyclic
loading. Both are expected to be recognized and identified by loss coefficients. Therefore, the loss
coefficient was determined by modal analysis of rods and fatigue specimen made of different materials
to correlate microstructural changes to attenuation. The determined loss coefficients indicated
microstructural changes in all materials investigated, confirming results from previous investigations
that showed an increasing attenuation due to cyclic loading for AISI 347. For the sonotrode materials
Z-M4 PM and Ferrotitanit WFN, the loss coefficients decreased due to thermal treatments. Technically
most relevant, changes in elastic modulus due to thermal treatments were quantitatively related to
frequency changes, which can significantly simplify future sonotrode development.
Seit 1993 veranstaltet der Fachbereich Mathematik der TU Kaiserslautern jährlich die mathematischen Modellierungswochen. Die Veranstaltung erwuchs parallel zu der steigenden Relevanz angewandter mathematischer Forschungsgebiete, wie der Technomathematik und der Wirtschaftsmathematik. Sie soll dazu dienen, Schülerinnen und Schülern die Bedeutung mathematischer Arbeitsweisen in der heutigen Berufswelt, insbesondere in Industrie und Wirtschaft, begreifbar zu machen. Darüber hinaus bietet die Modellierungswoche den teilnehmenden Lehrkräften einen Einblick in die Projektarbeit mit offenen Fragestellungen im Rahmen der mathematischen Modellierung. In diesem Report beschreiben wir die Projekte, die während der Modellierungswoche im Dezember 2021 durchgeführt wurden. Der Themenschwerpunkt der Veranstaltung lautete "Wetter und Katastrophenschutz".
Cyanobacteria are ubiquitous phototrophic prokaryotes that find a wide range of
applications in industry due to their broad product spectrum. In this context, the application
of cyanobacteria as biofertilizers and thus as an alternative to artificial fertilizers has emerged
in recent decades. The benefit is mostly based on the ability of cyanobacteria to fix elemental
nitrogen and make it available to the plants in a usable form. However, the positive effects of co-
cultivating plants with cyanobacteria are not limited to the provision of nitrogen. Cyanobacteria
produce numerous secondary metabolites that can be useful for plants, for example, they can
have growth-promoting effects or increase resistance to plant diseases. The effects of biotic
and abiotic stress can as well be reduced by many secondary metabolites. Furthermore, the
biofilms formed by the cyanobacteria can lead to improved soil conditions, such as increased
water retention capacity. To exchange the substances mentioned, cyanobacteria form symbioses
with plants, whereby the strength of the symbiosis depends on both partners, and not every
plant can form symbiosis with every cyanobacterium. Not only the plants in symbiosis benefit
from the cyanobacteria, but also vice versa. This review summarizes the beneficial effects of
cyanobacterial co-cultivation on plants, highlighting the substances exchanged and the strength
of cyanobacterial symbioses with plants. A detailed explanation of the mechanism of nitrogen
fixation in cyanobacterial heterocysts is given. Finally, a summary of possible applications of
co-cultivation in the (agrar-)industry is given.
The level of energy consumption in renovation activities of buildings has huge advantages
over the demolition of old buildings and the construction of new structures. Such renovation activities
are usually associated with the simultaneous strengthening of their elements, such as externally
bonded carbon fibre reinforced polymer (CFRP) lamellas or sheets on vertical and horizontal surfaces
as structural reinforcements. This means the process of refurbishing a building, as well as the
raw materials themselves have a significant impact on CO2 emissions and energy consumption.
This research paper demonstrates possibilities of replacing state of the art, highly energy-intensive
CFRP lamellas with basalt fibre reinforced plastics as energy-efficient structural reinforcements for
building constructions. The mechanical and thermal properties of basalt fibre reinforced polymer
(BFRP) composites with variable matrix formulations are investigated. The article considers macroand
microstructures of innovative BFRP. The investigations focus on fibre–matrix interactions with
different sizing formulations and their effect on the tensile strength, strain as well as modulus
of elasticity.
Precast concrete sandwich panels (PCSPs) are known for their good thermal, acoustic
and structural properties. Severe environmental demands can be met by PCSPs due to their use of
highly thermally insulating materials and non-metallic connectors. One of the main issues limiting
the wider use of sandwich walls in construction is their unknown fire resistance. Furthermore,
the actual behaviour of connectors and insulation in fire in terms of their mechanical performance
and their impact on fire spread and the fire resistance of walls is not fully understood. This paper
presents an experimental investigation on the structural and thermal behaviour of PCSPs with
mineral-wool insulation and glass-fiber-reinforced polymeric bar connectors coupling two concrete
wythes. Three full-size walls were tested following the REI certification test procedure for fire walls
under fire and vertical eccentric and post-fire mechanical impact load. The three test configurations
were adopted for the assessment of the connectors’ fire behaviour and its impact on the general
fire resistance of the walls. All the specimens met the REI 120-M criteria. The connectors did not
contribute to the fire’s spread and the integrity of the walls was maintained throughout the testing
time. This was also confirmed in the most unfavourable test configuration, in which some of the
connectors in the inner area of the wall were significantly damaged, and yet the structural connection
of the concrete wythes was maintained. The walls experienced heavy heat-induced thermal bowing.
The significant contribution of connectors to the stiffness of the wall during fire was observed and discussed.
Regelkonzept für eine Niederspannungsnetzautomatisierung unter Verwendung des Merit-Order-Prinzips
(2022)
Durch die zunehmende Erzeugungsleistung auf Niederspannungsnetzebene (NS-Netzebene) durch Photovoltaikanlagen, sowie die Elektrifizierung des Wärme- und des Verkehrssektors sind Investitionen in die NS-Netze notwendig. Ein höherer Digitalisierungsgrad im NS-Netz birgt das Potential, die notwendigen Investitionen genauer zu identifizieren, und damit ggf. zu reduzieren oder zeitlich zu verschieben. Hierbei stellt die Markteinführung intelligenter Messsysteme, sog. Smart Meter, eine neue Möglichkeit dar, Messwerte aus dem NS-Netz zu erhalten und auf deren Grundlage die Stellgrößen verfügbarer Aktoren zu optimieren. Dazu stellt sich die Frage, wie Messdaten unterschiedlicher Messzyklen in einem Netzautomatisierungssystem genutzt werden können und wie sich das nicht-lineare ganzzahlige Optimierungsproblem der Stellgrößenoptimierung effizient lösen lässt. Diese Arbeit befasst sich mit der Lösung des Optimierungsproblems. Dazu kommt eine Stellgrößenoptimierung nach dem Merit-Order-Prinzip zur Anwendung.
Due to the steadily increasing number of decentralized generation units, the upcoming smart meter rollout and the expected electrification of the transport sector (e-mobility), grid planning and grid operation at low-voltage (LV) level are facing major challenges. Therefore, many studies, research and demonstration projects on the above topics have been carried out in recent years, and the results and the methods developed have been published. However, the published methods usually cannot be replicated or validated, since the majority of the examination models or the scenarios used are incomprehensible to third parties. There is a lack of uniform grid models that map the German LV grids and can be used for comparative investigations, which are similar to the example of the North American distribution grid models of the IEEE. In contrast to the transmission grid, whose structure is known with high accuracy, suitable grid models for LV grids are difficult to map because of the high number of LV grids and distribution system operators. Furthermore, a detailed description of real LV grids is usually not available in scientific publications for data privacy
reasons. For investigations within a research project, the most characteristic synthetic LV grid models have been created, which are based on common settlement structures and usual grid planning principles in Germany. In this work, these LV grid models, and their development are explained in detail. For the first time, comprehensible LV grid models for the middle European area are available to the public, which can be used as a benchmark for further scientific research and method developments.
This document is an English version of the paper which was originally written in German1. In addition, this paper discusses a few more aspects especially on the planning process of distribution grids in Germany.
The move away from fossil fuels and the diversification of the primary energy sources used are imperative both in terms of mitigating global warming and ensuring the political independence of the Western world. For the industries of agriculture and forestry, it is possible to secure the basic energy supply through their own yield. The use of vegetable oil is a possibility to satisfy the energy requirements for agricultural machines both autonomously and sustainably. Up to now, rapeseed has been the most important plant for oil production in Western Europe. In the EU, rapeseed oil is currently credited with up to 60% fossil CO2 savings compared to conventional diesel fuel. As a result, since 2018, rapeseed oil is no longer considered as biofuel in the EU. However, if cultivation and processing are completely based on renewable energy sources, up to 90% of fossil CO2 emissions can be saved in the future. This also applies to rapeseed oil, which is a by-product of animal feed production. In addition, pure rapeseed oil is chemically unchanged and thus biodegradable, which makes it particularly attractive for use in environmentally sensitive areas.
To increase the attractiveness of rapeseed oil as a fuel for the agricultural industry, a multi-fuel concept for the flexible use of rapeseed oil, diesel fuel and any mixtures of these two fuels would be beneficial, as it minimizes economic risks due to price fluctuations, availability, and taxation. For implementing such a concept, technical adjustments to the propulsion system are necessary. In existing vegetable oil vehicles, cost-intensive additional components are required for diesel particulate filter regeneration. Conventional regeneration via post-injected fuel (which does not participate in combustion) leads to dilution of the engine oil with vegetable oil.
This study elaborates the possibilities of DPF regeneration in vegetable oil operation by internal engine measures without the need for post-injection. This includes strategies for generating exhaust gas temperatures in high-idle operation which are suitable for regeneration. For this purpose, strategies combining throttling and retarded combustion are used. The measures were successfully tested with respect to their effectiveness for DPF regeneration. It could also be proved that no increased engine oil dilution occurs as a result of the regeneration procedure.
For a prospective series application, however, regeneration should also be possible in transient engine operation. For this purpose, the measures developed for high-idle regeneration have been transferred to partial load points to gain insight into their applicability for transient engine operation. In addition, the effect of external EGR on regeneration has been considered. As the previous investigations of high-idle regeneration showed that regeneration is most critical when pure rapeseed oil is used, the studies of regeneration in part-load operation were limited to pure rapeseed oil. The systematic parameter variations carried out during the studies helped to improve the understanding of the system and the mechanisms of regeneration. The results of the investigation show that the exhaust gas temperature can be increased significantly by the measures studied. However, achieving the exhaust temperature required for DPF regeneration remains a challenge for certain operating points.
A novel portable low-cost Arduino-controlled photo- and fluorimeter for on-site measurements has been developed. The device uses LEDs as a light source and a phototransistor as a light sensor. The circuit is based on the discharge of a capacitor with the photocurrent from the phototransistor. Validation experiments for absorbance measurements were performed by measuring protein concentration using the Bradford method and measuring phosphate ions in water using a commercial test kit. The emission light of the excited fluorescent dyes rhodamine 6G and calcofluor white was measured to validate the usability of the device as a fluorescence photometer. In all validation experiments, similar correlation coefficients and limit of detection could be achieved with the portable photo- and fluorimeter and a laboratory spectrometer and fluorimeter. Real sample analysis was performed, measuring phosphate concentration in freshwater and concentration of green fluorescent protein, extracted from Escherichia coli.
A thermo-mechanical treatment (TMT) at the temperature of maximum dynamic strain
aging has been optimized and performed on quenched and tempered steel SAE4140H (German
designation: 42CrMo4) in order to improve the fatigue limit in the high cycle fatigue (HCF) and and
very high cycle fatigue (VHCF) regimes. Fatigue tests, with ultimate cycle numbers of 107 and 109,
have shown that the TMT can increase both the fatigue lifetime and the fatigue limit in the HCF
and VHCF regimes. The increased stress intensity factors of the critical inclusions after the TMT
indicate that the effect can be attributed to a stabilized microstructure around critical crack-initiating
inclusions through the locking of edge dislocations by carbon atoms during the TMT
In this paper, a prediction model for the tensile behaviour of ultra-high performance
fibre-reinforced concrete is proposed. It is based on integrating force contributions of all fibres
crossing the crack plane. Piecewise linear models for the force contributions depending on fibre
orientation and embedded length are fitted to force–slip curves obtained in single-fibre pull-out tests.
Fibre characteristics in the crack are analysed in a micro-computed tomography image of a concrete
sample. For more general predictions, a stochastic fibre model with a one-parametric orientation
distribution is introduced. Simple estimators for the orientation parameter are presented, which only
require fibre orientations in the crack plane. Our prediction method is calibrated to fit experimental
tensile curves.
The number of sensors used in modern devices is rapidly increasing, and the interaction with sensors demands analog-to-digital data conversion (ADC). A conventional ADC in leading-edge technologies faces
many issues due to signal swings, manufacturing deviations, noise, etc. Designers of ADCs are moving to the
time domain and digital designs techniques to deal with these issues. This work pursues a novel self-adaptive
spiking neural ADC (SN-ADC) design with promising features, e.g., technology scaling issues, low-voltage
operation, low power, and noise-robust conditioning. The SN-ADC uses spike time to carry the information.
Therefore, it can be effectively translated to aggressive new technologies to implement reliable advanced sensory electronic systems. The SN-ADC supports self-x (self-calibration, self-optimization, and self-healing) and
machine learning required for the internet of things (IoT) and Industry 4.0. We have designed the main part of
SN-ADC, which is an adaptive spike-to-digital converter (ASDC). The ASDC is based on a self-adaptive complementary metal–oxide–semiconductor (CMOS) memristor. It mimics the functionality of biological synapses,
long-term plasticity, and short-term plasticity. The key advantage of our design is the entirely local unsupervised
adaptation scheme. The adaptation scheme consists of two hierarchical layers; the first layer is self-adapted, and
the second layer is manually treated in this work. In our previous work, the adaptation process is based on 96 variables. Therefore, it requires considerable adaptation time to correct the synapses’ weight. This paper proposes a
novel self-adaptive scheme to reduce the number of variables to only four and has better adaptation capability
with less delay time than our previous implementation. The maximum adaptation times of our previous work
and this work are 15 h and 27 min vs. 1 min and 47.3 s. The current winner-take-all (WTA) circuits have issues, a
high-cost design, and no identifying the close spikes. Therefore, a novel WTA circuit with memory is proposed.
It used 352 transistors for 16 inputs and can process spikes with a minimum time difference of 3 ns. The ASDC
has been tested under static and dynamic variations. The nominal values of the SN-ADC parameters’ number
of missing codes (NOMCs), integral non-linearity (INL), and differential non-linearity (DNL) are no missing
code, 0.4 and 0.22 LSB, respectively, where LSB stands for the least significant bit. However, these values are
degraded due to the dynamic and static deviation with maximum simulated change equal to 0.88 and 4 LSB and
6 codes for DNL, INL, and NOMC, respectively. The adaptation resets the SN-ADC parameters to the nominal
values. The proposed ASDC is designed using X-FAB 0.35 µm CMOS technology and Cadence tools.
The Influence of Case and Word Order in Child and Adult
Processing of Relative Clauses in Greek
(2022)
Previous cross-linguistic studies have shown that object relative clauses (ORCs) are typically harder to parse than subject relative clauses (SRCs). The cause of difficulty, however, is still under debate, both in the adult and in the developmental literature. The present study investigates the on-line processing of SRCs and ORCs in Greek-speaking 11- to 12-year-old children and adults, and provides evidence on relative clause processing in Greek—a free word order language. We conducted a self-paced listening task in which we manipulated the type of relative clause (SRC vs. ORC), the RC internal word order (canonical vs. scrambled), and the type of relativizer (relative pronoun vs. complementizer). The results showed that SRCs were overall processed faster than ORCs, providing evidence that children follow similar processing strategies to adults. In addition, accusative case marking facilitated the processing of non-canonical structures in adults but less so in children. Children showed heavy reliance on word order, as they processed nominative and accusative pre-verbal NPs in exactly the same way, while they were strongly garden-pathed in ORCs with post-verbal nominative NPs. We argue that these results are compatible with the Competition Model.
The spike protein is the major protein on the surface of coronaviruses. It is therefore the prominent target of neutralizing antibodies and consequently the antigen of all currently admitted vaccines against SARS-CoV-2. Since it is a 1,273-amino acids glycoprotein with 22 N-linked glycans, the production of functional, full-length spike protein was limited to higher eukaryotes. Here we report the production of full-length SARS-CoV-2 spike protein – lacking the C-terminal membrane anchor – as a secreted protein in the prefusion-stabilized conformation in the unicellular green alga Chlamydomonas reinhardtii. We show that the spike protein is efficiently cleaved at the furin cleavage site during synthesis in the alga and that cleavage is abolished upon mutation of the multi-basic cleavage site. We could enrich the spike protein from culture medium by ammonium sulfate precipitation and demonstrate its functionality based on its interaction with recombinant ACE2 and ACE2 expressed on human 293T cells. Chlamydomonas reinhardtii is a GRAS organism that can be cultivated at low cost in simple media at a large scale, making it an attractive production platform for recombinant spike protein and other biopharmaceuticals in low-income countries.
A flexible operation of multiple robotic manipulators operating in a dynamic environment
requires online trajectory planning to ensure collision-free trajectories. In this work, we propose a real-time
capable motion control algorithm, based on nonlinear model predictive control, which accounts for static and
dynamic obstacles. The proposed algorithm is realized in a distributed scheme, where each robot optimizes its
own trajectory with respect to the related objective and constraints.We propose a novel approach for collision
avoidance between multiple robotic manipulators, where each robot accounts for the predicted movement of
the neighboring robots. Additionally, we propose a method to reliably detect and resolve deadlocks occurring
in a setup of multiple robotic manipulators.We validate our approach on pick and place scenarios involving
multiple robotic manipulators operating in a common workspace in a realistic simulation environment
set up in Gazebo. The robots are controlled using the Robot Operating System. Our approach scales up
to 4 manipulators and computes a path for each robot in a simultaneous pick and place operation in 94% of
all investigated cases without deadlock detection and 100 % of cases with the proposed deadlock resolution
algorithm. In contrast, the investigated conventional path planners, such as PRM, PRM*, CHOMP and RRTConnect,
successfully plan a trajectory in at most 54% of all investigated cases for a simultaneous operation
of 4 robotic manipulators hindering their application in setups of multiple manipulators.
Thermal comfort is one of the most important factors for occupant satisfaction and, as a result, for the building energy performance. Decentralized heating and cooling systems, also known as “Personal Environmental Comfort Systems” (PECS), have attracted significant interest in research and industry in recent years. While building simulation software is used in practice to improve the energy performance of buildings, most building simulation applications use the PMV approach for comfort calculations. This article presents a newly developed building controller that uses a holistic approach in the consideration of PECS within the framework of the building simulation software Esp-r. With PhySCo, a dynamic physiology, sensation, and comfort model, the presented building controller can adjust the setpoint temperatures of the central HVAC system as well as control the use of PECS based on the thermal sensation and comfort values of a virtual human. An adaptive building controller with a wide dead-band and adaptive setpoints between 18 to 26 °C (30 °C) was compared to a basic controller with a fixed and narrow setpoint range between 21 to 24 °C. The simulations were conducted for temperate western European climate (Mannheim, Germany), classified as Cfb climate according to Köppen-Geiger. With the adaptive controller, a 12.5% reduction in end-use energy was achieved in winter. For summer conditions, a variation between the adaptive controller, an office chair with a cooling function, and a fan increased the upper setpoint temperature to 30 °C while still maintaining comfortable conditions and reducing the end-use energy by 15.3%. In spring, the same variation led to a 9.3% reduction in the final energy. The combinations of other systems were studied with the newly presented controller.
Simulation of Particle Interaction with Surface Microdefects during Cold Gas-Dynamic Spraying
(2022)
The cold gas-dynamic spray (CGDS) technique is utilized for repairing processes of a
large number of metallic components in mechanical and process engineering, such as bridges or
vehicles. Fine particles impacting on the component surface can be severely deformed and penetrate
into the defects, filling and coating them, resulting in possible protection against corrosion or crack
propagation. This work focuses on the investigation of the impact behavior of cold sprayed particles
with the wall surface having microdefects in the form of cavities. The collision of fine single particles
with the substrate, both made from AISI 1045 steel, was simulated with the finite element method
(FEM) using the Johnson–Cook failure model. The impact phenomena of particles on different
microdefect geometries were obtained and compared with the collision on a smooth surface. The
particle diameter and defect were varied to investigate the influence of the size on the deformation
behaviour. The different impact scenarios result in different temperature and stress distributions in
the contact zone, penetration and deformation behavior during the collision.
In recent years, the utilization of dual-fuel combustion has gained
popularity in order to improve engine efficiency and emissions. With
its high knock resistance, methane allows operation in high
compression diesel engines with lower risk of knocking. With the use
of diesel fuel as an ignition source, it is possible to exploit the
advantages of lean combustion without facing problems to provide
the high amount of ignition energy necessary to burn methane under
such operating conditions. Another advantage is the variety of
sources from which the primary fuel can be obtained. In addition to
fossil sources, methane can also be produced from biomass or
electrical energy.
As the rate of substitution of diesel by methane increases, the trade-
off between nitrogen oxide and soot is mitigated. However, emissions
of carbon monoxide and unburned methane increase. Since carbon
monoxide is toxic and methane has 25 times the global warming
potential of carbon dioxide, these emission components pose a
problem. Because of the stability of the molecule, methane catalysts
require an exhaust gas temperature of over 500 °C in order to work
effectively.
In this work, the effect of conventional cooled external exhaust gas
recirculation (EGR) and additional hot internal EGR are investigated
for different substitution rates in a nonroad tractor engine converted
to dual-fuel operation. The internal EGR rate is controlled by a
variable second exhaust valve lift during the intake stroke – an
approach which promises to benefit dual-fuel engines by increasing
the in-cylinder gas temperature, thus favoring more complete
combustion. A simulation model of the engine is used to determine
the internal EGR rates and in-cylinder temperatures based on the
experimental data. When internal EGR is used in combination with
external EGR, the resulting emissions show additional reductions in
nitrogen oxide (up to -51 %), carbon monoxide (up to -18 %) and
methane (up to -28 %) with increasing internal EGR, while still
maintaining low soot levels due to the substitution of diesel fuel for
methane.
In this work, steady-state droplet size distributions in a DN300 stirred batch vessel with a
Rushton turbine impeller are investigated using an insertion probe based on the telecentric transmit-
ted light principle. High-resolution droplet size distributions are extracted from the images using
a convolutional neural network for image-analysis in order to investigate the influence of impeller
speed and phase fraction (up to 50 vol.-%). In addition, Sauter mean diameters were calculated and
correlated with two semi-empirical approaches, while the standard approach only accomplished 5.7%
accuracy, and the correlation of Laso et al. provided a relative mean error of 4.0%. In addition, the
correlated exponent in the Weber number was fitted to the experimental data of this work yielding a
slightly different value than the theoretical (−0.6), which allows a better representation of the low
coalescence tendency of the system, which is usually neglected in standard procedures.
Visual–graphical representations are used to visualise information and are therefore key components of learning materials. An important type of convention-based representation in everyday contexts as well as in science, technology, engineering, and math (STEM) disciplines are vector field plots. Based on the cognitive theory of multimedia learning, we aim to optimize an instruction with symbolical-mathematical and visual-graphical representations in undergraduate physics education through spoken instruction combined with dynamic visual cues. For this purpose, we conduct a pre-post study with 38 natural science students who are divided into two groups and instructed via different modalities and with visual cues on the graphical interpretation of vector field plots. Afterward, the students rate their cognitive load. During the computer-based experiment, we record the participants’ eye movements. Our results indicate that students with spoken instruction perform better than students with written instruction. This suggests that the modality effect is also applicable to mathematical-symbolical and convention-based visual-graphical representations. The differences in visual strategies imply that spoken instruction might lead to increased effort in organising and integrating information. The finding of the modality effect with higher performance during spoken instruction could be explained by deeper cognitive processing of the material.
The effects of shrinkage can be manifold. Vacant green areas are a typical manifestation of shrinkage in deindustrialized cities, such as Heerlen, Netherlands. Such challenges are usually managed by the municipality which, due to financial reasons, often has to turn to citizens to aid in accommodating those effects. The example of Gebrookerbos in Heerlen shows how an adaptation of governance processes can take place in order to facilitate the involvement of citizens in reusing vacant spaces. The introduction of the position of account manager as well as brooker are being regarded as essential for shortening the distance between municipality and citizens as well as contributing to replacing the mistrust towards the municipality, which is in line with existing research on depopulating areas. Further, making a plethora of funding options and projects available for
civic initiatives ensures the longevity of civic involvement. Finally, the findings show how working on the “hardware”, the visible vacancy and deterioration of the land—by adapting the “software”,
the institutional set up and focusing on civic empowerment—of a shrinking city can go hand in hand.
A potential fucoidan-based PEGylated PLGA nanoparticles (NPs) offering a proper delivery of N-methyl anthranilic acid (MA, a model of hydrophobic anti-inflammatory drug) have been
developed via the formation of fucoidan aqueous coating surrounding PEGylated PLGA NPs. The optimum formulation (FuP2) composed of fucoidan:m-PEG-PLGA (1:0.5 w/w) with particle size(365 ± 20.76 nm), zeta potential (-22.30 ± 2.56 mV), % entrapment efficiency (85.45 ± 7.41), drug loading (51.36 ± 4.75 µg/mg of NPs), % initial burst (47.91 ± 5.89), and % cumulative release
(102.79 ± 6.89) has been further investigated for the anti-inflammatory in vivo study. This effect of
FuP2 was assessed in rats’ carrageenan-induced acute inflammation model. The average weight of the
paw edema was significantly lowered (p ≤ 0.05) by treatment with FuP2. Moreover, cyclooxygenase-2 and tumor necrosis factor-alpha immunostaining were decreased in FuP2 treated group compared to the other groups. The levels of prostaglandin E2, nitric oxide, and malondialdehyde were significantly
reduced (p ≤ 0.05) in the FuP2-treated group. A significant reduction (p ≤ 0.05) in the expression
of interleukins (IL-1b and IL-6) with an improvement of the histological findings of the paw tissues was observed in the FuP2-treated group. Thus, fucoidan-based PEGylated PLGA–MA NPs are a promising anti-inflammatory delivery system that can be applied for other similar drugs potentiating their pharmacological and pharmacokinetic properties.
Qualitative NMR spectroscopic and quantitative calorimetric binding studies were performed to characterize the interaction of nontoxic mimics of the V-type nerve agent VX (O-ethyl S-[2-(diisopropylamino)ethyl] methylphosphonothioate) and the Novichok nerve agent A-234 (ethyl (1-(diethylamino)ethylidene)phosphoramidofluoridate) with a series of receptors in 100 mM aqueous phosphate buffer at pH 7.4 and 37°C. These investigations provided information about the preferred geometry with which the nerve agent mimics are included into the receptor cavities and about the stability of the complexes formed. According to the results, the positively charged VX mimic prefers to bind to cation receptors such as sulfonated calixarenes and an acyclic cucurbituril but does not noticeably interact with cyclodextrins. While binding to the acyclic cucurbituril is stronger than that to calixarenes, the mode of inclusion into the sulfonatocalix[4]arene cavity is better suited for the development of scavengers that bind and detoxify V-type nerve agents. The neutral Novichok mimic, on the other hand, only interacts with the acyclic cucurbituril with a strength required for scavenger development. These binding studies thus provided guidelines for the further development of nerve agent scavengers.
In the face of the Covid‐19 crisis, the city model of the new Leipzig Charter of the EU was re‐evaluated. The existing urban
development model of a mixed and compact city is to be mainly maintained because the urban density or building typology
does not influence the spread of Covid‐19. But the pandemic has made it clear how important green space and recreation
areas are for inner city residential areas. This green space also becomes more important regarding climate adaptation
measures to provide cooler air and ventilation. In the framework of the Leipzig Charter of the EU, the German ministry
for building adopted the memorandum on Urban Resilience in May 2021. Resilience in this context means that we should
not only repair the damage of disasters but also adapt to future crises and make our cities more resilient and sustainable.
For this, we need to strengthen preventive strategies in urban development planning connected with urban renewal
approaches and ask for extended city models. Planning shapes the future, including counteracting undesirable scenarios
with preventive planning. In this sense, future planning and disaster control have common objectives—they take an interdisciplinary
approach to prepare for future change, they want to anticipate and prevent danger, protect and expand the
infrastructure, and serve the common good. In this article, I will point out how integrated urban development concepts
should be extended with aspects of urban resilience, and which city models are important for the future.
Many practical optimisation problems have conflicting objectives, which should be addressed by multi-criteria optimisation (MCO), i.e. by determining the set of best compromises, the Pareto set (PS), along with its picture in parameter space (PSPS). In previous work on low-dimensional MCO problems, we have found characteristic topological features of the PS and PSPS, which depend on the dimensionality of the parameter space M and the objective space N. E.g., M = 2 and N = 3 yields triangles with needle-like extensions. The reasons for these topological features were unknown so far. Here, we show that they are to be expected if all objective functions of the MCO satisfy two conditions: (a) they can be approximated by quadratic functions and (b) one of the eigenvalues of the Hessian matrix evaluated at the function’s minimum is small compared to the other eigenvalues. Objective functions which meet conditions (a) and (b) have a valley-like topology, for which the valley lies in the direction of the eigenvector corresponding to the lowest eigenvalue. The PSPS can be estimated by starting at the minimum of an objective function, following the valley, and combining these lines for all objective functions. The PS is obtained by evaluating the objective functions. We believe that the conditions (a) and (b) are met in many practical problems and discuss an example from molecular modelling. The improved understanding of the features of these MCO problems opens the route for designing methods for swiftly finding estimates of their PS and PSPS.
This contribution defends two claims. The first is about why thought experiments are so relevant and powerful in mathematics. Heuristics and proof are not strictly and, therefore, the relevance of thought experiments is not contained to heuristics. The main argument is based on a semiotic analysis of how mathematics works with signs. Seen in this way, formal symbols do not eliminate thought experiments (replacing them by something rigorous), but rather provide a new stage for them. The formal world resembles the empirical world in that it calls for exploration and offers surprises. This presents a major reason why thought experiments occur both in empirical sciences and in mathematics. The second claim is about a looming aporia that signals the limitation of thought experiments. This aporia arises when mathematical arguments cease to be fully accessible, thus violating a precondition for experimenting in thought. The contribution focuses on the work of Vladimir Voevodsky (1966–2017, Fields medalist in 2002) who argued that even very pure branches of mathematics cannot avoid inaccessibility of proof. Furthermore, he suggested that computer verification is a feasible path forward, but only if proof is not modeled in terms of formal logic.
The dynamic behaviour of unsaturated sand rubber chips mixtures at various gravimetric contents is evaluated through an experimental study comprising resonant column tests in a fixed-free device. Chips were irregularly shaped with dimensions ranging from 5 to 14 mm. Three types of sand with different gradation have been considered. Relative density amounted to 0.5 for all specimens. Due to the large size of the chips, the diameter of the specimens had to be equal to 100 mm, which in turn required a re-calibration of the device assuming a frequency-dependent drive head inertia. The effects of confining stress, rubber chips content, and sand gradation on shear modulus and damping ratio are determined over wide ranges of the shear strain. At small strains, as known for sands, increasing the confining stress stiffens the mixtures. Increasing the rubber chips content reduces significantly the shear modulus and increases the damping ratio. At higher strains, increasing the confining stress or the rubber content flattens the reduction of the shear modulus with strain. Damping at high strains does not show any appreciable dependence on rubber content. Unloading–reloading sequences are used to assess shear modulus degradation and threshold strains. Finally, design equations are derived from the test results to predict the dynamic response of the composite material.
Synthetic Biology is revolutionizing biological research by introducing principles of mechanical engineering, including the standardization of genetic parts and standardized part assembly routes. Both are realized in the Modular Cloning (MoClo) strategy. MoClo allows for the rapid and robust assembly of individual genes and multigene clusters, enabling iterative cycles of gene design, construction, testing, and learning in short time. This is particularly true if generation times of target organisms are short, as is the case for the unicellular green alga Chlamydomonas reinhardtii. Testing a gene of interest in Chlamydomonas with MoClo requires two assembly steps, one for the gene of interest itself and another to combine it with a selection marker. To reduce this to a single assembly step, we constructed five new destination vectors. They contain genes conferring resistance to commonly used antibiotics in Chlamydomonas and a site for the direct assembly of basic genetic parts. The vectors employ red/white color selection and, therefore, do not require costly compounds like X-gal and IPTG. mCherry expression is used to demonstrate the functionality of these vectors.
We consider the optimization problem of a large insurance company that wants to maximize the expected utility of its surplus through the optimal control of the proportional reinsurance. In addition, the insurer is exposed to the risk of default of its reinsurer at the worst possible time, a setting that is closely related to a scenario of the Swiss Solvency Test.
In a widely-studied class of multi-parametric optimization problems, the objective value of each solution is an affine function of real-valued parameters. Then, the goal is to provide an optimal solution set, i.e., a set containing an optimal solution for each non-parametric problem obtained by fixing a parameter vector. For many multi-parametric optimization problems, however, an optimal solution set of minimum cardinality can contain super-polynomially many solutions. Consequently, no polynomial-time exact algorithms can exist for these problems even if P=NP. We propose an approximation method that is applicable to a general class of multi-parametric optimization problems and outputs a set of solutions with cardinality polynomial in the instance size and the inverse of the approximation guarantee. This method lifts approximation algorithms for non-parametric optimization problems to their parametric version and provides an approximation guarantee that is arbitrarily close to the approximation guarantee of the approximation algorithm for the non-parametric problem. If the non-parametric problem can be solved exactly in polynomial time or if an FPTAS is available, our algorithm is an FPTAS. Further, we show that, for any given approximation guarantee, the minimum cardinality of an approximation set is, in general, not ℓ-approximable for any natural number ℓ less or equal to the number of parameters, and we discuss applications of our results to classical multi-parametric combinatorial optimizations problems. In particular, we obtain an FPTAS for the multi-parametric minimum s-t-cut problem, an FPTAS for the multi-parametric knapsack problem, as well as an approximation algorithm for the multi-parametric maximization of independence systems problem.
Comparative public policy is a blooming research area. It also suffers from some curious blind spots. In this paper we discuss four of these: (1) the obsession with covariance, which means that important phenomena are ignored; (2) the lack of agency, which leads to underwhelming explanatory models; (3) the unclear universe of cases, which means the inferential value of theories and the empirical results are unclear; and (4) the focus on outputs, even though most theories contain strong assumptions about the political process leading to certain outputs. Following this discussion, we then outline how a closer integration of policy process theories may be fruitful for future research.
Algorithmic systems that provide services to people by supporting or replacing human decision-making promise greater convenience in various areas. The opacity of these applications, however, means that it is not clear how much they truly serve their users. A promising way to address the issue of possible undesired biases consists in giving users control by letting them configure a system and aligning its performance with users’ own preferences. However, as the present paper argues, this form of control over an algorithmic system demands an algorithmic literacy that also entails a certain way of making oneself knowable: users must interrogate their own dispositions and see how these can be formalized such that they can be translated into the algorithmic system. This may, however, extend already existing practices through which people are monitored and probed and means that exerting such control requires users to direct a computational mode of thinking at themselves.
We examine the predictability of 299 capital market anomalies enhanced by 30 machine learning approaches and over 250 models in a dataset with more than 500 million firm-month anomaly observations. We find significant monthly (out-of-sample) returns of around 1.8–2.0%, and over 80% of the models yield returns equal to or larger than our linearly constructed baseline factor. For the best performing models, the risk-adjusted returns are significant across alternative asset pricing models, considering transaction costs with round-trip costs of up to 2% and including only anomalies after publication. Our results indicate that non-linear models can reveal market inefficiencies (mispricing) that are hard to conciliate with risk-based explanations.
The simulation of Dynamic Random Access Memories (DRAMs) on system level requires highly accurate models due to their complex timing and power behavior. However, conventional cycle-accurate DRAM subsystem models often become a bottleneck for the overall simulation speed. A promising alternative are simulators based on Transaction Level Modeling, which can be fast and accurate at the same time. In this paper we present DRAMSys4.0, which is, to the best of our knowledge, the fastest and most extensive open-source cycle-accurate DRAM simulation framework. DRAMSys4.0 includes a novel software architecture that enables a fast adaption to different hardware controller implementations and new JEDEC standards. In addition, it already supports the latest standards DDR5 and LPDDR5. We explain how to apply optimization techniques for an increased simulation speed while maintaining full temporal accuracy. Furthermore, we demonstrate the simulator’s accuracy and analysis tools with two application examples. Finally, we provide a detailed investigation and comparison of the most prominent cycle-accurate open-source DRAM simulators with regard to their supported features, analysis capabilities and simulation speed.
First essential m-dissipativity of an infinite-dimensional Ornstein-Uhlenbeck operator N, perturbed by the gradient of a potential, on a domain FC
∞
b
of finitely based, smooth and bounded functions, is shown. Our considerations allow unbounded diffusion operators as coefficients. We derive corresponding second order regularity estimates for solutions f of the Kolmogorov equation ◂−▸αf−Nf=g, ◂+▸α∈(0,∞), generalizing some results of Da Prato and Lunardi. Second, we prove essential m-dissipativity for generators (◂,▸LΦ,FC
∞
b
) of infinite-dimensional degenerate diffusion processes. We emphasize that the essential m-dissipativity of (◂,▸LΦ,FC
∞
b
) is useful to apply general resolvent methods developed by Beznea, Boboc and Röckner, in order to construct martingale/weak solutions to infinite-dimensional non-linear degenerate stochastic differential equations. Furthermore, the essential m-dissipativity of (◂,▸LΦ,FC
∞
b
) and (◂,▸N,FC
∞
b
), as well as the regularity estimates are essential to apply the general abstract Hilbert space hypocoercivity method from Dolbeault, Mouhot, Schmeiser and Grothaus, Stilgenbauer, respectively, to the corresponding diffusions.
We provide a complete elaboration of the L2-Hilbert space hypocoercivity theorem for the degenerate Langevin dynamics with multiplicative noise, studying the longtime behavior of the strongly continuous contraction semigroup solving the abstract Cauchy problem for the associated backward Kolmogorov operator. Hypocoercivity for the Langevin dynamics with constant diffusion matrix was proven previously by Dolbeault, Mouhot and Schmeiser in the corresponding Fokker–Planck framework and made rigorous in the Kolmogorov backwards setting by Grothaus and Stilgenbauer. We extend these results to weakly differentiable diffusion coefficient matrices, introducing multiplicative noise for the corresponding stochastic differential equation. The rate of convergence is explicitly computed depending on the choice of these coefficients and the potential giving the outer force. In order to obtain a solution to the abstract Cauchy problem, we first prove essential self-adjointness of non-degenerate elliptic Dirichlet operators on Hilbert spaces, using prior elliptic regularity results and techniques from Bogachev, Krylov and Röckner. We apply operator perturbation theory to obtain essential m-dissipativity of the Kolmogorov operator, extending the m-dissipativity results from Conrad and Grothaus. We emphasize that the chosen Kolmogorov approach is natural, as the theory of generalized Dirichlet forms implies a stochastic representation of the Langevin semigroup as the transition kernel of a diffusion process which provides a martingale solution to the Langevin equation with multiplicative noise. Moreover, we show that even a weak solution is obtained this way.
This article presents a methodology whereby adjoint solutions for partitioned multiphysics problems can be computed efficiently, in a way that is completely independent of the underlying physical sub-problems, the associated numerical solution methods, and the number and type of couplings between them. By applying the reverse mode of algorithmic differentiation to each discipline, and by using a specialized recording strategy, diagonal and cross terms can be evaluated individually, thereby allowing different solution methods for the generic coupled problem (for example block-Jacobi or block-Gauss-Seidel). Based on an implementation in the open-source multiphysics simulation and design software SU2, we demonstrate how the same algorithm can be applied for shape sensitivity analysis on a heat exchanger (conjugate heat transfer), a deforming wing (fluid–structure interaction), and a cooled turbine blade where both effects are simultaneously taken into account.
Additive manufacturing (AM) enables the production of components with a high degree of individualization at constant manufacturing effort, which is why additive manufacturing is increasingly applied in industrial processes. However, additively produced surfaces do not meet the requirements for functional surfaces, which is why subsequent machining is mandatory for most of AM-workpieces. Further, the performance of many functional surfaces can be enhanced by microstructuring. The combination of both AM and subtractive processes is referred to as hybrid manufacturing. In this paper, the hybrid manufacturing of AISI 316L is investigated. The two AM technologies laser-based powder bed fusion (L-PBF) and high-speed laser directed energy deposition (HS L-DED) are used to produce workpieces which are subsequently machined by micro milling (tool diameter d = 100 µm). The machining results were evaluated based on tool wear, burr formation, process forces and the generated topography. Those indicated differences in the machinability of materials produced by L-PBF and HS L-DED which were attributed to different microstructural properties.
The present study aimed to assess the effects of asymmetric muscle fatigue on the skin surface temperature of abdominal and back muscles. The study was based on a pre-post/follow-up design with one group and included a total of 41 subjects (22 male, 19 female; age, 22.63 ± 3.91; weight, 71.89 ± 12.97 kg; height, 173.36 ± 9.95). All the participants were asked to perform side bends in sets of 20 repetitions on a Roman chair until complete exhaustion. The pre-, post- and follow-up test (24 h after) skin surface temperatures were recorded with infrared thermography. Subjective muscle soreness and muscle fatigue were analyzed using two questionnaires. The results of the post hoc tests showed that skin temperature was statistically significantly lower in the post-tests than in the pre- and follow-up tests, but no meaningful differences existed between the pre- and follow-up tests. Asymmetric side differences were found in the post-test for the upper and lower areas of the back. Differences were also noted for the front in both the upper and lower areas. No thermographic side asymmetries were found at the pre- or follow-up measurement for either the back or the front. Our results support the potential of using thermographic skin surface temperature to monitor exercise and recovery in athletes, as well as its use in rehabilitational exercise selection.
In this paper, we devise a stochastic asset–liability management (ALM) model for a life insurance company and analyze its influence on the balance sheet within a low-interest rate environment. In particular, a flexible procedure for the generation of insurers’ compressed contract portfolios that respects the given biometric structure is presented, extending the existing literature on stochastic ALM modeling. The introduced balance sheet model is in line with the principles of double-entry bookkeeping as required in accounting. We further focus on the incorporation of new business, i.e. the addition of newly concluded contracts and thus of insured in each period. Efficient simulations are obtained by integrating new policies into existing cohorts according to contract-related criteria. We provide new results on the consistency of the balance sheet equations. In extensive simulation studies for different scenarios regarding the business form of today’s life insurers, we utilize these to analyze the long-term behavior and the stability of the components of the balance sheet for different asset–liability approaches. Finally, we investigate the robustness of two prominent investment strategies against crashes in the capital markets, which lead to extreme liquidity shocks and thus threaten the insurer’s financial health.