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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.