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Die Digitale Transformation, u.a. getrieben durch die weithin sichtbare Vision der Industrie 4.0, gilt als eine der großen Herausforderungen unserer Zeit. Insbesondere für den Wirtschaftsstandort Deutschland ergibt sich die Frage, wie KMU auf diese Transformation nicht nur vorbereitet, sondern auch bei deren Bewältigung durch Wissenstransfer aus Hochschulen heraus unter-stützt werden können. Die Vorteile, die dabei ein digitaler Wissenstransfer - Stichwort z.B. „e-Learning“ - bieten können, passen augenscheinlich gut zu den Charakteristika und Bedürfnissen von KMU. Es entstehen jedoch auch spezifische Herausforderungen. Diese liegen sowohl darin, in einer dynamischen Umgebung Themen zu identifizieren, die für die Unternehmen wichtig und interessant sind als auch in vielfältigen Akzeptanzproblematiken auf der Inhaltsebene und auch bezogen auf die Methoden des Wissenstransfers. Die hier vorgestellten Erkenntnisse, basierend auf einer Umfrage und Expertengesprächen im Rahmen des - durch den ESF und den Freistaat Bayern geförderten - mainproject2018. Sie zeigen, dass Wissenstransfer zum digitalen Wandel wohl auch aber nicht alleine durch digitale Methoden gestaltet werden kann. Denn bevor dieser von den eigentlichen Adressaten akzeptiert und genutzt wird, müssen fundamentale Vorbehalte und Widerstände abgebaut werden. Es werden daher neben den Ergebnissen der empirischen Untersuchung auch erste Überlegungen zu akzeptanzfördernden Maßnahmen im o.g. Kontext vorgestellt und diskutiert.
This contribution discusses the integration of polymer planar Bragg grating sensors (PPBG) into carbon fiber reinforced polymer (CFRP) components. For the first time, it is shown that PPBGs based on cyclic olefin copolymers can be integrated into commercial-grade composites, thereby withstanding the demanding production processes. Pre-impregnated fibers are stacked and partially modified to form a sensor pocket. Afterwards, the CFRP specimen containing the optical sensor is cured in a heated mechanical press for 2 hours at a pressure of 7 bar and a temperature of 120 °C. A subsequent evalutaion of the sensor signal shows a Bragg wavelength shift of 1236 pm and a decline in signal amplitude of -2 dB. Three-point flexural tests of the cured sample reveal a linear behavior of the sensor signal towards external loads. The determined sensitivity in dependence of the CFRP specimen's maximum central deflection is -112 pm/mm, while correlation to the applied force results in a sensitivity of -5 pm/N.
Introduction
There is evidence that SARS-CoV2 has a particular affinity for kidney tissue and is often
associated with kidney failure.
Methods
We assessed whether proteinuria can be predictive of kidney failure, the development of
chronic kidney disease, and mortality in 37 critically ill COVID-19 patients. We used machine
learning (ML) methods as decision trees and cut-off points created by the OneR package to
add new aspects, even in smaller cohorts.
Results
Among a total of 37 patients, 24 suffered higher-grade renal failure, 20 of whom required kidney
replacement therapy. More than 40% of patients remained on hemodialysis after intensive
care unit discharge or died (27%). Due to frequent anuria proteinuria measured in two-thirds of
the patients, it was not predictive for the investigated endpoints; albuminuria was higher in
patients with AKI 3, but the difference was not significant. ML found cut-off points of >31.4 kg/
m2 for BMI and >69 years for age, constructed decision trees with great accuracy, and identified
highly predictive variables for outcome and remaining chronic kidney disease.
Conclusions
Different ML methods and their clinical application, especially decision trees, can provide
valuable support for clinical decisions. Presence of proteinuria was not predictive of CKD or
AKI and should be confirmed in a larger cohort.
Continuous glucose monitoring (CGM) improves treatment with lower blood glucose levels
and less patient effort. In combination with continuous insulin application, glycemic control
improves and hypoglycemic episodes should decrease. Direct feedback of CGM to continuous
subcutaneous insulin application, using an algorithm is called a closed-loop (CL)
artificial pancreas system. Commercial devices stop insulin application by predicting hypoglycemic
blood glucose levels through direct interaction between the sensor and pump. The
prediction is usually made for about 30 minutes and insulin delivery is restarted at the previous
level if a rise in blood glucose is predicted within the next 30 minutes (hybrid closed loop
system, HCL this is known as a predictive low glucose suspend system (PLGS)). In a fully
CL system, sensor and pump communicate permanently with each other. Hybrid closedloop
(HCL) systems, which require the user to estimate the meal size and provide a meal
insulin basis, are commercially available in Germany at the moment. These systems result
in fewer hyperglycemic and hypoglycemic episodes with improved glucose control. Open
source initiatives have provided support by building do-it-yourself CL (DIYCL) devices for
automated insulin application since 2014, and are used by a tech-savvy subgroup of
patients. The first commercial hybrid CL system has been available in Germany since September
2019. We surveyed 1054 patients to determine which devices are currently used,
which features would be in demand by potential users, and the benefits of DIYCL systems.
9.7% of these used a DIYCL system, while 50% would most likely trust these systems but
more than 85% of the patients would use a commercial closed loop system, if available. The
DIYCL users had a better glucose control regarding their time in range (TIR) and glycated
hemoglobin (HbA1c).
In the light of the information age, information overload research in new areas (e.g., social media, virtual collaboration) rises rapidly in many fields of research in business administration with a variety of methods and subjects. This review article analyzes the development of information overload literature in business administration and related interdisciplinary fields and provides a comprehensive and overarching overview using a bibliometric literature analysis combined with a snowball sampling approach. For the last decade, this article reveals research directions and bridges of literature in a wide range of fields of business administration (e.g., accounting, finance, health management, human resources, innovation management, international management, information systems, marketing, manufacturing, or organizational science). This review article identifies the
major papers of various research streams to capture the pulse of the information overload-related research and suggest new questions that could be addressed in the future and identifies concrete open gaps for further research. Furthermore, this article presents a new framework for structuring information overload issues which extends our understanding of influence factors and effects of information overload in the decision-making process.
In this article, we contribute to the longstanding debate among economists regarding the question of “nature or nurture” with respect to economics students’ attitudes toward various allocation mechanisms for a scarce resource. While previous research starts the debate by beginning with first-year economics students, we aim to evaluate pre-firstyear individuals, i.e., school pupils. Drawing on the seminal works of Haucap, J., & Just, T. (2010). Not guilty? Another look at the nature and nurture of economics students. European Journal of Law and Economics, 29(2), 239–254 and Frey, B. S., Pommerehne,W.W., & Gygi, B. (1993). Economics indoctrination or selection? Some empirical results. The Journal of Economic Education, 24(3), 271–281, we investigate a sample of pupils ranging from the 5th to the 13th grades to determine whether pupils are “born economists” (nature), develop economic thinking (nurture), or both. We find that young individuals start to think differently in early grades and that their thinking and attitudes are shaped differently throughout their school careers, thereby providing support for the effects of both nature and nurture. Our findings show that school time impacts fairness judgments, particularly regarding price mechanisms. Regarding learning or indoctrination, we find that economics-inclined pupils are positively affected by lessons in economics in school, while pupils who are economics-averse draw completely diametric conclusions from economics lessons, thereby exhibiting increased disapproval of price allocation over the course of these classes and increased approval of the first come, first served and governmental action mechanisms.Moreover, we find strong effects of gender and migration background in this context. This study is the first to elucidate the development of economic thinking in 5th–13th grade pupils. Our results are important for economists, educators,
and researchers because they can serve as a starting point for subsequent investigations in this under-researched field.
Erste Schritte zur Implementierung eines Nachhaltigkeitsmanagements im Unternehmen
Dieser kompakte Band geht auf zentrale Prinzipien und Konzepte ein, die Unternehmen helfen, ein Nachhaltigkeitsmanagement aufzubauen und weiterzuentwickeln. Darüber hinaus bietet er einen Überblick über die verschiedenen Ansätze und Instrumente des Nachhaltigkeitsmanagements, damit Unternehmen ihre Aktivitäten analysieren, bewerten und verbessern können, um ökologische und soziale Auswirkungen zu reduzieren und langfristige Wertschöpfung zu ermöglichen.
Diese grundlegende Einführung richtet sich an die Führungskräfte in den Unternehmen, die sich mit Fragen des Umwelt- und Nachhaltigkeitsmanagements beschäftigen. Zunächst werden die relevanten normativen und regulativen Anforderungen an das unternehmerische Nachhaltigkeitsmanagement vorgestellt, bevor konkret erste Schritte zur Implementierung eines Nachhaltigkeitsmanagements entwickelt werden. Die beiden letzten Kapitel stellen ein geeignetes Steuerungssystem sowie die Grundlagen der Nachhaltigkeitskommunikation eines Unternehmens vor.
Chaoticity Versus Stochasticity in Financial Markets: Are Daily S&P 500 Return Dynamics Chaotic?
(2021)
In this study, we present a combinatory chaos analysis of daily wavelet-filtered (denoised) S&P 500 returns (2000–2020) compared with respective surrogate datasets, Brownian motion returns and a Lorenz system realisation. We show that the dynamics of the S&P 500 return series consist of an almost equally divided combination of stochastic and deterministic chaos. The strange attractor of the S&P 500 return system is graphically displayed via Takens’ embedding and by spectral embedding in combination with Laplacian Eigenmaps. For the field of nonlinear and financial chaos research, we present a bibliometric analysis paired with citation network analysis. We critically discuss implications and future prospects.
This experimental study analyzes how a key factor, information load, influences decision making in escalation situations, i.e., in situations in which decision mak- ers reinvest further resources in a losing course of action, even when accounting information indicates that the project is performing poorly and should be discontin- ued. This study synthesizes prior escalation research with information overload and investigates how different levels of information load influence the escalation of com- mitment. Our findings reveal a U-shaped effect of information load: When decision makers face negative feedback, a higher information load mitigates the escalation tendency up to a certain point. However, beyond this point, more information rein- forces the escalation tendency. Moreover, we find that the type of feedback affects self-justification, and we find a negative and significant interaction between informa- tion load and self-justification in negative-feedback cases. Thus, studies investigat- ing escalation of commitment should control for self-justification and information load when utilizing high levels of information load. Finally, in the positive-feedback condition, higher information load encourages decision makers to continue promis- ing courses of action, i.e., increases decision-making performance.