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In der Dissertationsschrift wird der Einfluss von Kosten, Steuern und Sterblichkeit auf die Vorteilhaftigkeit der Riester-Rente aus einzelwirtschaftlicher Perspektive modelltheoretisch untersucht. Die Arbeit ist dabei zweigeteilt. Während sich der erste Teil insbesondere mit den Auswirkungen von Kosten in der Ansparphase der Riester-Rente und damit auf die Investitionsentscheidung eines Riester-Sparers beschäftigt, wird im zweiten Teil im Speziellen die Auszahlungsphase unter besonderer Berücksichtigung von Sterblichkeitsaspekten behandelt.
Im Detail lassen sich die wichtigsten Ergebnisse der Hauptkapitel im jeweils gewählten Modellrahmen wie folgt thesenartig zusammenfassen:
Aufgrund der staatlichen Förderungen und der Reglementierung bezüglich der Verrechnung der Abschluss- und Vertriebskosten im AltZertG erweisen sich eine klassische Riester-Rentenversicherung sowie ein Riester-Banksparplan auch bei Einbezug von Kosten direkt vergleichbaren, ungeförderten Anlagealternativen überlegen (Kapitel 3).
Die Doppelbelastung mit Einmalkosten im Zeitpunkt des Vertragsabschlusses sorgt dafür, dass der Wechsel eines Riester-Anbieters nur bei entsprechend hohen Kostenentlastungen beim Neuanbieter vorteilhaftig ist (Kapitel 4). Bei einer klassischen Riester-Rentenversicherung sind hierfür prozentual gesehen wesentlich höhere Entlastungen erforderlich als bei fondsgestützten Anlageprodukten. Die Einführung eines Kostenkoeffizienten unterstützt den Anleger bei der Wechselentscheidung nur in der Produktart der klassischen Rentenversicherungen, den fondsgestützten Produkten lässt sich aufgrund der Wechselwirkung zwischen übertragenem Vermögen und Kosten kein eindeutiger Koeffizient zuordnen.
Unter der Annahme vollständiger Sicherheit auf Seiten des Anlegers kann ein kritischer Kapitalmarktzinssatz berechnet werden, oberhalb dessen eine schädliche Verwendung des angesparten Riester-Vermögens einer rentenförmigen Auszahlung vorgezogen wird (Kapitel 7). Eine Verwendung des geförderten Vermögens für die Altersvorsorge ist somit letztlich nicht garantiert. Je jünger dabei der Anleger im Zeitpunkt des Vertragsabschlusses ist, desto geringer fällt der kritische Kapitalmarktzins aus.
Wird ein risikoneutraler Anleger unterstellt, dessen individuelle Sterblichkeit dem vom Statistischen Bundesamt prognostizierten Bevölkerungsdurchschnitt entspricht, so ist die Riester-Rente aufgrund der langen Förderungsdauer besonders für junge Anleger der Unterlassensalternative überlegen (Kapitel 8). Allerdings zieht die Mehrzahl der untersuchten Anleger, deren Sterblichkeit im Bevölkerungsdurchschnitt liegt, eine schädliche Verwendung des Riester-geförderten Altersvorsorgevermögens einer gesetzlich vorgeschriebenen, rentenförmigen Kapitalisierung vor.
Sozioökonomische Faktoren beeinflussen in Abhängigkeit von der tatsächlichen Ausprägung der Sterblichkeitsdifferenzen entscheidend die Vorteilhaftigkeit der Riester-Rente (Kapitel 9). Neben der geringeren finanziellen Bildung und der Anrechnung der Rentenleistungen aus der Riester-Anlage auf die Grundsicherung im Alter kann dies als Erklärungsansatz dafür herangezogen werden, dass Gering-verdiener in der Grundgesamtheit der Riester-Sparer eher unterrepräsentiert sind.
The DREAM complex plays an important role in regulation of gene expression during the cell cycle. We have previously shown that the DREAM subunit LIN9 is required for early embryonic development and for the maintenance of the inner cell mass in vitro. In this study we examined the effect of knocking down LIN9 on ESCs. We demonstrate that depletion of LIN9 alters the cell cycle distribution of ESCs and results in an accumulation of cells in G2 and M and in an increase of polyploid cells. Genome-wide expression studies showed that the depletion of LIN9 results in downregulation of mitotic genes and in upregulation of differentiation-specific genes. ChIP-on chip experiments showed that mitotic genes are direct targets of LIN9 while lineage specific markers are regulated indirectly. Importantly, depletion of LIN9 does not alter the expression of pluripotency markers SOX2, OCT4 and Nanog and LIN9 depleted ESCs retain alkaline phosphatase activity. We conclude that LIN9 is essential for proliferation and genome stability of ESCs by activating genes with important functions in mitosis and cytokinesis.
The increasing prevalence of smart mobile devices (e.g., smartphones) enables the combined use of mobile crowdsensing (MCS) and ecological momentary assessments (EMA) in the healthcare domain. By correlating qualitative longitudinal and ecologically valid EMA assessment data sets with sensor measurements in mobile apps, new valuable insights about patients (e.g., humans who suffer from chronic diseases) can be gained. However, there are numerous conceptual, architectural and technical, as well as legal challenges when implementing a respective software solution. Therefore, the work at hand (1) identifies these challenges, (2) derives respective recommendations, and (3) proposes a reference architecture for a MCS-EMA-platform addressing the defined recommendations. The required insights to propose the reference architecture were gained in several large-scale mHealth crowdsensing studies running for many years and different healthcare questions. To mention only two examples, we are running crowdsensing studies on questions for the tinnitus chronic disorder or psychological stress. We consider the proposed reference architecture and the identified challenges and recommendations as a contribution in two respects. First, they enable other researchers to align our practical studies with a baseline setting that can satisfy the variously revealed insights. Second, they are a proper basis to better compare data that was gathered using MCS and EMA. In addition, the combined use of MCS and EMA increasingly requires suitable architectures and associated digital solutions for the healthcare domain.
Process model comprehension is essential in order to understand the five Ws (i.e., who, what, where, when, and why) pertaining to the processes of organizations. However, research in this context showed that a proper comprehension of process models often poses a challenge in practice. For this reason, a vast body of research exists studying the factors having an influence on process model comprehension. In order to point research towards a neuro-centric perspective in this context, the paper at hand evaluates the appropriateness of measuring the electrodermal activity (EDA) during the comprehension of process models. Therefore, a preliminary test run and a feasibility study were conducted relying on an EDA and physical activity sensor to record the EDA during process model comprehension. The insights obtained from the feasibility study demonstrated that process model comprehension leads to an increased activity in the EDA. Furthermore, EDA-related results indicated significantly that participants were confronted with a higher cognitive load during the comprehension of complex process models. In addition, the experiences and limitations we learned in measuring the EDA during the comprehension of process models are discussed in this paper. In conclusion, the feasibility study demonstrated that the measurement of the EDA could be an appropriate method to obtain new insights into process model comprehension.
Process models are crucial artifacts in many domains, and hence, their proper comprehension is of importance. Process models mediate a plethora of aspects that are needed to be comprehended correctly. Novices especially face difficulties in the comprehension of process models, since the correct comprehension of such models requires process modeling expertise and visual observation capabilities to interpret these models correctly. Research from other domains demonstrated that the visual observation capabilities of experts can be conveyed to novices. In order to evaluate the latter in the context of process model comprehension, this paper presents the results from ongoing research, in which gaze data from experts are used as Eye Movement Modeling Examples (EMMEs) to convey visual observation capabilities to novices. Compared to prior results, the application of EMMEs improves process model comprehension significantly for novices. Novices achieved in some cases similar performances in process model comprehension to experts. The study's insights highlight the positive effect of EMMEs on fostering the comprehension of process models.
Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July 2020) in eight languages and attracted 7290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures.
The Internet of Things (IoT) enables a variety of smart applications, including smart home, smart manufacturing, and smart city. By enhancing Business Process Management Systems with IoT capabilities, the execution and monitoring of business processes can be significantly improved. Providing a holistic support for modeling, executing and monitoring IoT-driven processes, however, constitutes a challenge. Existing process modeling and process execution languages, such as BPMN 2.0, are unable to fully meet the IoT characteristics (e.g., asynchronicity and parallelism) of IoT-driven processes. In this article, we present BPMNE4IoT—A holistic framework for modeling, executing and monitoring IoT-driven processes. We introduce various artifacts and events based on the BPMN 2.0 metamodel that allow realizing the desired IoT awareness of business processes. The framework is evaluated along two real-world scenarios from two different domains. Moreover, we present a user study for comparing BPMNE4IoT and BPMN 2.0. In particular, this study has confirmed that the BPMNE4IoT framework facilitates the support of IoT-driven processes.