Open Access

This study presents a gender-focused perspective of entrepreneurship education programs, aiming to understand variations in entrepreneurial intention, reasoning on entrepreneurship, self-efficacy, and entrepreneurial education preferences. The present research grounds on Entrepreneurial Event Theory to examine entrepreneurial intention, desirability, and feasibility in the context of entrepreneurship education. The research was conducted in Germany in 2021 and included a sample of 156 university students. The study deploys the Mann-Whitney U Test to examine gender differences among university students regarding entrepreneurship. The findings highlight a heightened perception of risk among female students, influencing their focus on positive/negative entrepreneurial events compared to male students. Moreover, the research reveals a greater inclination among females to engage in both curricular and extracurricular entrepreneurship education activities, corroborating previous studies suggesting greater benefits for female students in such programs. The study also underscores the importance of distinguishing between curricular and extracurricular offerings, indicating promising avenues for future entrepreneurship education research. Overall, this investigation contributes new insights and explanations regarding gender dynamics in entrepreneurship education, shedding light on potential areas for further exploration in the field.

Push notifications are widely used in Android apps to show users timely and potentially sensitive information outside the apps’ regular user interface. Google’s default service for sending push notifications, Firebase Cloud Messaging (FCM), provides only transport layer security and does not offer app developers message protection schemes to prevent access or detect modifications by the push notification service provider or other intermediate systems.We present and discuss an in-depth mixed-methods study of push notification message security and privacy in Android apps. We statically analyze a representative set of 100,000 up-to-date and popular Android apps from Google Play to get an overview of push notification usage in the wild. In an in-depth follow-up analysis of 60 apps, we gain detailed insights into the leaked content and what some developers do to protect the messages. We find that (a) about half of the analyzed apps use push notifications, (b) about half of the in-depth analyzed messaging apps do not protect their push notifications, allowing access to sensitive data that jeopardizes users’ security and privacy and (c) the means of protection lack a standardized approach, manifesting in various developer-defined encryption schemes, custom protocols, or out-of-band communication methods. Our research highlights gaps in developer-centric security regarding appropriate technologies and supporting measures that researchers and platform providers should address.

The air quality in many German cities does not comply with EU-wide standards. Vehicle emissions, in particular, have been identified as an important cause of air pollution. As a result, driving bans for diesel vehicles with critical pollutant groups have been imposed by courts in many places in recent history. Against the backdrop of the growth of major German cities over the last few years, the question has become whether and how a change in the modal split in favor of more environmentally and climate-friendly public transport sector can be achieved. The Federal City of Bonn is one of five model cities that is testing measures to reduce traffic-related nitrogen dioxide emissions through a Climate Ticket as a mobility flat rate for one year for 365 €, which is part of the two-year "Lead City" project funded by the federal government. A quantitative survey (n = 1,315) of Climate Ticket users as well as the logistic regression carried out confirm that a change in individual mobility behavior in favor of public transport is possible by subsidizing the ticket price. The results show that individual traffic could be saved on the city's main congestion axes. In order to achieve a sustainable improvement in air quality, such a Climate Ticket must be granted on a permanent basis, with a well-designed mobility offer and must be generous in terms of the group of authorized persons and the area of validity.

A building’s energy storage demand depends on a variety of factors related to the specific local conditions such as building type, self-sufficiency-rate, and grid connection. Here, a newly developed bottom-up procedure is presented for classifying buildings in an urban building portfolio according to specific criteria. The algorithm uses publicly available building data such as building use, ground floor area, roof ridge height, solar roof potential, and population statistics. In addition, it considers the local gas grid (GG) as well as the district heating (DH) network. The building classification is developed for identifying typical building situations that can be used to estimate the demand for residential energy storage capacity. The developed algorithm is used to identify potential implementation of private photovoltaic(PV)-metal-hydride-storage (MHS) systems, for three scenarios, into the urban infrastructure for the city of Cologne. As result the statistical confidence interval of all analyzed buildings regarding their classification as well as corresponding maps is shown. Since similar data sets as used are available for many German or European metropolitan areas, the method developed with the assumptions presented in this work, can be used for classification of other urban and semi-urban areas including the assessment of their grid infrastructure.

Um ein Power-to-Gas-to-X-System effizient zu optimieren, kann ein digitaler Zwilling als Simulationsmodell auf Basis experimenteller Daten für ein Laborsystem erstellt und entsprechend verändert werden. Darüber hinaus müssen für die Überwachung des realen Systems bzw. die Online-Simulation kontinuierlich Daten aus Experiment und Simulation erfasst und verarbeitet werden. Insgesamt ist ein effizienter Datenmanagement-Workflow erforderlich. In dieser Arbeit wird ein Workflow aus freier, etablierter und skalierbarer Open-Source-Software für die vorliegende Anwendung skizziert und insbesondere ein geeignetes Datenmodell entwickelt, implementiert und seine ressourcensparende Realisierung auf kostengünstiger Hardware gezeigt. Abhängig von der Datenmodellierung kann preiswerte und alte Hardware für die geforderte Aufgabe ausreichend sein. Mit Apache NiFi wird ein visueller Workflow zum Abrufen und Verarbeiten von Daten aus verschiedenen Quellen geschaffen. Die extrahierten Daten werden in Apache Cassandra aggregiert, einem Datensystem, das aufgrund seiner Leistung, Skalierbarkeit und Haltbarkeit häufig verwendet wird. Grafana wird zur visuellen Überwachung des Systems eingesetzt. Das gesamte System wird mit Hilfe von Docker-Containern aufgebaut zum Zwecke der Reproduzierbarkeit und effizienten Bereitstellung. Benchmarks und realistische Hardware- und Datenmodellierungskonfigurationen demonstrieren die Leistung der vorgeschlagenen Lösung.

The digitization of financial activities in consumers' lives is increasing, and the digitalization of invoicing processes is expected to play a significant role, although this area is not well understood regarding the private sector. Human-Computer Interaction (HCI) and Computer Supported Cooperative Work (CSCW) research have a long history of analyzing the socio-material and temporal aspects of work practices that are relevant for the domestic domain. The socio-material structuring of invoicing work and the working styles of consumers must be considered when designing effective consumer support systems. In this ethnomethodologically-informed, design-oriented interview study, we followed 17 consumers in their daily practices of dealing with invoices to make the invisible administrative work involved in this process visible. We identified and described the meaningful artifacts that were used in a spatial-temporal process within various storage locations such as input, reminding, intermediate (for postponing cases) buffers, and archive systems. Furthermore, we identified three different working styles that consumers exhibited: direct completion, at the next opportunity, and postpone as far as possible. This study contributes to our understanding of household economics and domestic workplace studies in the tradition of CSCW and has implications for the design of electronic invoicing systems.

During robot-assisted therapy, a robot typically needs to be partially or fully controlled by therapists, for instance using a Wizard-of-Oz protocol; this makes therapeutic sessions tedious to conduct, as therapists cannot fully focus on the interaction with the person under therapy. In this work, we develop a learning-based behaviour model that can be used to increase the autonomy of a robot’s decision-making process. We investigate reinforcement learning as a model training technique and compare different reward functions that consider a user’s engagement and activity performance. We also analyse various strategies that aim to make the learning process more tractable, namely i) behaviour model training with a learned user model, ii) policy transfer between user groups, and iii) policy learning from expert feedback. We demonstrate that policy transfer can significantly speed up the policy learning process, although the reward function has an important effect on the actions that a robot can choose. Although the main focus of this paper is the personalisation pipeline itself, we further evaluate the learned behaviour models in a small-scale real-world feasibility study in which six users participated in a sequence learning game with an assistive robot. The results of this study seem to suggest that learning from guidance may result in the most adequate policies in terms of increasing the engagement and game performance of users, but a large-scale user study is needed to verify the validity of that observation.

Solar photovoltaic power output is modulated by atmospheric aerosols and clouds and thus contains valuable information on the optical properties of the atmosphere. As a ground-based data source with high spatiotemporal resolution it has great potential to complement other ground-based solar irradiance measurements as well as those of weather models and satellites, thus leading to an improved characterisation of global horizontal irradiance. In this work several algorithms are presented that can retrieve global tilted and horizontal irradiance and atmospheric optical properties from solar photovoltaic data and/or pyranometer measurements. The method is tested on data from two measurement campaigns that took place in the Allgäu region in Germany in autumn 2018 and summer 2019, and the results are compared with local pyranometer measurements as well as satellite and weather model data. Using power data measured at 1 Hz and averaged to 1 min resolution along with a non-linear photovoltaic module temperature model, global horizontal irradiance is extracted with a mean bias error compared to concurrent pyranometer measurements of 5.79 W m−2 (7.35 W m−2) under clear (cloudy) skies, averaged over the two campaigns, whereas for the retrieval using coarser 15 min power data with a linear temperature model the mean bias error is 5.88 and 41.87 W m−2 under clear and cloudy skies, respectively. During completely overcast periods the cloud optical depth is extracted from photovoltaic power using a lookup table method based on a 1D radiative transfer simulation, and the results are compared to both satellite retrievals and data from the Consortium for Small-scale Modelling (COSMO) weather model. Potential applications of this approach for extracting cloud optical properties are discussed, as well as certain limitations, such as the representation of 3D radiative effects that occur under broken-cloud conditions. In principle this method could provide an unprecedented amount of ground-based data on both irradiance and optical properties of the atmosphere, as long as the required photovoltaic power data are available and properly pre-screened to remove unwanted artefacts in the signal. Possible solutions to this problem are discussed in the context of future work.

Vehicle emissions have been identified as a cause of air pollution and one of the major reasons why air quality in many large German cities such as Berlin, Bonn, Hamburg, Cologne or Munich does not meet EU-wide limits. As a result, in the recent past, judicial driving bans on diesel vehicles have been imposed in many places since those vehicles emit critical pollutant groups. For the increasing urban population, the challenge is whether and how a change of the modal split in favor of the more environmentally and climate-friendly public transport can be achieved. This paper presents the case of the Federal City of Bonn, one of five model cities sponsored by the German federal government that are testing measures to reduce traffic-related pollutant emissions by expanding the range of public transport services on offer. We present the results of a quantitative survey (N = 14,296) performed in the Bonn/Rhein-Sieg area and the neighboring municipalities as well as the ensuing logistic regressions confirming that a change in individual mobility behavior in favor of public transport is possible through expanding services. Our results show that individual traffic could be reduced, especially on the city's main traffic axes. To sustainably improve air quality, such services must be made permanently available.

Neutral buoyancy has been used as an analog for microgravity from the earliest days of human spaceflight. Compared to other options on Earth, neutral buoyancy is relatively inexpensive and presents little danger to astronauts while simulating some aspects of microgravity. Neutral buoyancy removes somatosensory cues to the direction of gravity but leaves vestibular cues intact. Removal of both somatosensory and direction of gravity cues while floating in microgravity or using virtual reality to establish conflicts between them has been shown to affect the perception of distance traveled in response to visual motion (vection) and the perception of distance. Does removal of somatosensory cues alone by neutral buoyancy similarly impact these perceptions? During neutral buoyancy we found no significant difference in either perceived distance traveled nor perceived size relative to Earth-normal conditions. This contrasts with differences in linear vection reported between short- and long-duration microgravity and Earth-normal conditions. These results indicate that neutral buoyancy is not an effective analog for microgravity for these perceptual effects.

Many students approaching adulthood often choose high-calorie food products. Concurrently, health interventions applied during this life phase can potentially lead to a healthier lifestyle. Nudge health interventions in experimental cafeteria settings have been found to improve eating behavior effectively, yet research in real-world settings is lacking. Accepting nudges as health interventions impacts nudge effectiveness. The present study applies a pretest–posttest design for a period of three consecutive weeks (no nudge, nudge, no nudge), testing the effectiveness of the so-called Giacometti cue on the number of calories purchased in a real-world cafeteria. Students were exposed to the nudge during the intervention week when entering the cafeteria and when choosing their meals. After purchasing a meal, their choice was recorded, and they completed a questionnaire. The Giacometti cue immediately reduced the number of calories purchased (comparing weeks one and two). After nudge removal, an effect was identified, increasing the number of calories purchased (comparing weeks two and three). Contrary to expectations, higher nudge acceptance resulted in more calories purchased. Neither awareness of the nudge’s presence when buying food nor the interaction between acceptance and awareness played a role. We explore potential explanations for the Giacometti cue’s effects.

Monitoring the content of dissolved ozone in purified water is often mandatory to ensure the appropriate levels of disinfection and sanitization. However, quantification bears challenges as colorimetric assays require laborious off-line analysis, while commercially available instruments for electrochemical process analysis are expensive and often lack the possibility for miniaturization and discretionary installation. In this study, potentiometric ionic polymer metal composite (IPMC) sensors for the determination of dissolved ozone in ultrapure water (UPW) systems are presented. Commercially available polymer electrolyte membranes are treated via an impregnation-reduction method to obtain nanostructured platinum layers. By applying 25 different synthesis conditions, layer thicknesses of 2.2 to 12.6 µm are obtained. Supporting radiographic analyses indicate that the platinum concentration of the impregnation solution has the highest influence on the obtained metal loading. The sensor response behavior is explained by a Langmuir pseudo-isotherm model and allows the quantification of dissolved ozone to trace levels of less than 10 µg L−1. Additional statistical evaluations show that the expected Pt loading and radiographic blackening levels can be predicted with high accuracy and significance (R2adj. > 0.90, p < 10−10) solely from given synthesis conditions.

Background Consumers rely heavily on online user reviews when shopping online and cybercriminals produce fake reviews to manipulate consumer opinion. Much prior research focuses on the automated detection of these fake reviews, which are far from perfect. Therefore, consumers must be able to detect fake reviews on their own. In this study we survey the research examining how consumers detect fake reviews online. Methods We conducted a systematic literature review over the research on fake review detection from the consumer-perspective. We included academic literature giving new empirical data. We provide a narrative synthesis comparing the theories, methods and outcomes used across studies to identify how consumers detect fake reviews online. Results We found only 15 articles that met our inclusion criteria. We classify the most often used cues identified into five categories which were (1) review characteristics (2) textual characteristics (3) reviewer characteristics (4) seller characteristics and (5) characteristics of the platform where the review is displayed. Discussion We find that theory is applied inconsistently across studies and that cues to deception are often identified in isolation without any unifying theoretical framework. Consequently, we discuss how such a theoretical framework could be developed.

In young adulthood, important foundations are laid for health later in life. Hence, more attention should be paid to the health measures concerning students. A research field that is relevant to health but hitherto somewhat neglected in the student context is the phenomenon of presenteeism. Presenteeism refers to working despite illness and is associated with negative health and work-related effects. The study attempts to bridge the research gap regarding students and examines the effects of and reasons for this behavior. The consequences of digital learning on presenteeism behavior are moreover considered. A student survey (N = 1036) and qualitative interviews (N = 11) were conducted. The results of the quantitative study show significant negative relationships between presenteeism and health status, well-being, and ability to study. An increased experience of stress and a low level of detachment as characteristics of digital learning also show significant relationships with presenteeism. The qualitative interviews highlighted the aspect of not wanting to miss anything as the most important reason for presenteeism. The results provide useful insights for developing countermeasures to be easily integrated into university life, such as establishing fixed learning partners or the use of additional digital learning material.

Despite the long history of fingerprint biometrics and its use to authenticate individuals, there are still some unsolved challenges with fingerprint acquisition and presentation attack detection (PAD). Currently available commercial fingerprint capture devices struggle with non-ideal skin conditions, including soft skin in infants. They are also susceptible to presentation attacks, which limits their applicability in unsupervised scenarios such as border control. Optical coherence tomography (OCT) could be a promising solution to these problems. In this work, we propose a digital signal processing chain for segmenting two complementary fingerprints from the same OCT fingertip scan: One fingerprint is captured as usual from the epidermis (“outer fingerprint”), whereas the other is taken from inside the skin, at the junction between the epidermis and the underlying dermis (“inner fingerprint”). The resulting 3D fingerprints are then converted to a conventional 2D grayscale representation from which minutiae points can be extracted using existing methods. Our approach is device-independent and has been proven to work with two different time domain OCT scanners. Using efficient GPGPU computing, it took less than a second to process an entire gigabyte of OCT data. To validate the results, we captured OCT fingerprints of 130 individual fingers and compared them with conventional 2D fingerprints of the same fingers. We found that both the outer and inner OCT fingerprints were backward compatible with conventional 2D fingerprints, with the inner fingerprint generally being less damaged and, therefore, more reliable.

The following work presents algorithms for semi-automatic validation, feature extraction and ranking of time series measurements acquired from MOX gas sensors. Semi-automatic measurement validation is accomplished by extending established curve similarity algorithms with a slope-based signature calculation. Furthermore, a feature-based ranking metric is introduced. It allows for individual prioritization of each feature and can be used to find the best performing sensors regarding multiple research questions. Finally, the functionality of the algorithms, as well as the developed software suite, are demonstrated with an exemplary scenario, illustrating how to find the most power-efficient MOX gas sensor in a data set collected during an extensive screening consisting of 16,320 measurements, all taken with different sensors at various temperatures and analytes.

Due to the COVID-19 pandemic, health education programs and workplace health promotion (WHP) could only be offered under difficult conditions, if at all. In Germany for example, mandatory lockdowns, working from home, and physical distancing have led to a sharp decline in expenditure on prevention and health promotion from 2019 to 2020. At the same time, the pandemic has negatively affected many people’s mental health. Therefore, our goal was to examine audiovisual stimulation as a possible measure in the context of WHP, because its usage is contact-free, time flexible, and offers, additionally, voice-guided health education programs. In an online survey following a cross-sectional single case study design with 393 study participants, we examined the associations between audiovisual stimulation and mental health, work engagement, and burnout. Using multiple regression analyses, we could identify positive associations between audiovisual stimulation and mental health, burnout, and work engagement. However, longitudinal data are needed to further investigate causal mechanisms between mental health and the use of audiovisual stimulation. Nevertheless, especially with regard to the pandemic, audiovisual stimulation may represent a promising measure for improving mental health at the workplace.

Research has identified nudging as a promising and effective tool to improve healthy eating behavior in a cafeteria setting. However, it remains unclear who is and who is not “nudgeable” (susceptible to nudges). An important influencing factor at the individual level is nudge acceptance. While some progress has been made in determining influences on the acceptance of healthy eating nudges, research on how personal characteristics (such as the perception of social norms) affect nudge acceptance remains scarce. We conducted a survey on 1032 university students to assess the acceptance of nine different types of healthy eating nudges in a cafeteria setting with four influential factors (social norms, health-promoting collaboration, responsibility to promote healthy eating, and procrastination). These factors are likely to play a role within a university and a cafeteria setting. The present study showed that key influential factors of nudge acceptance were the perceived responsibility to promote healthy eating and health-promoting collaboration. We also identified three different student clusters with respect to nudge acceptance, demonstrating that not all nudges were accepted equally. In particular, default, salience, and priming nudges were at least moderately accepted regardless of the degree of nudgeability. Our findings provide useful policy implications for nudge development by university, cafeteria, and public health officials. Recommendations are formulated for strengthening the theoretical background of nudge acceptance and the susceptibility to nudges.