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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.