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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.
Die moderne Arbeitswelt erfordert digitale Kompetenz, doch Hochschulen mangelt es an Angeboten zum digitalen Kompetenzaufbau Studierender. Peer-Angebote können ein sinnvoller Ansatz zur Förderung digitaler Kompetenz sein, allerdings fehlen empirische Belege für deren Wirksamkeit. Die Studie setzt hier an und evaluiert den digitalen Kompetenzerwerb von Teilnehmenden fachübergreifender Peer-Trainings auf Grundlage des DigComp Rahmenmodells. Die Ergebnisse zeigen, dass Trainings-Teilnehmende ihre digitale Kompetenz im Vergleich zur Kontrollgruppe signifikant stärker steigern konnten. Die Ausbildung zur bzw. zum Peer-Trainer:in sowie die Peer-Trainings wurden von allen Beteiligten sehr positiv bewertet.
INTRODUCTION: The cardiac magnetic resonance (CMR) data on mid- to long-term myocardial damage due to COVID-19 infections in elite athletes are scarce. Therefore, this study investigated the mid -to long-term consequences of myocardial involvement after a COVID-19 infection in elite athletes.
MATERIALS AND METHODS: This study included 27 athletes at the German Olympic Centre North Rhine-Westphalia (NRW)/Rhineland with a confirmed previous COVID-19 infection between January 2020 and October 2021. The athletes were part of an ongoing observational COVID-19 study at the Institute of Cardiology and Sports Medicine Cologne at the German Sport University (DSHS).Nine healthy non-athletes with no prior COVID-19 illness served as controls. CMR was performed within a mean of 182 days (standard deviation [SD] 99) of the initial positive test result.
RESULTS: CMR did not reveal any signs of acute myocarditis (according to the current Lake Louise criteria) or myocardial damage in any of the 26 elite athletes with previous COVID-19 infection. Of these athletes, 92% experienced a symptomatic course, and 54% reported symptoms lasting for more than 4 weeks. One male athlete was excluded from the analysis because CMR revealed an arrhythmogenic right ventricular cardiomyopathy (ARVC). Athletes had significantly enlarged left and right ventricle volumes and increased left ventricular myocardial mass in comparison to the healthy control group (LVEDVi 103.4 vs 91.1 ml/m2, p = 0.031; RVEDVi 104.1 vs 86.6 ml/m2, p = 0.007; LVMi 59.0 vs 46.2 g/m2, p = 0.002). Only two cases of elevated high-sensitivity-Troponin were documented; in one, the participant had previously engaged in high-intensity training, and in the other, CMR revealed a diagnosis of an arrhythmogenic cardiomyopathy.
CONCLUSION: Our findings suggest that the risk for mid- to long-term myocardial damage is very low to negligible in elite athletes. Our results do not allow conclusions to be drawn regarding myocardial injury in the acute phase of infection nor about possible long-term myocardial effects in the general population.
Green infrastructure has been widely recognized for the benefits to human health and biodiversity conservation. However, knowledge of the qualities and requirements of such spaces and structures for the effective delivery of the range of ecosystem services expected is still limited, as well as the identification of trade-offs between services. In this study, we apply the One Health approach in the context of green spaces to investigate how urban park characteristics affect human mental health and wildlife support outcomes and identify synergies and trade-offs between these dimensions. Here we show that perceived restorativeness of park users varies significantly across sites and is mainly affected by safety and naturalness perceptions. In turn, these perceptions are driven by objective indicators of quality, such as maintenance of facilities and vegetation structure, and subjective estimations of biodiversity levels. The presence of water bodies benefited both mental health and wildlife. However, high tree canopy coverage provided greater restoration potential whereas a certain level of habitat heterogeneity was important to support a wider range of bird species requirements. To reconcile human and wildlife needs in green spaces, cities should strategically implement a heterogeneous green infrastructure network that considers trade-offs and maximizes synergies between these dimensions.
Improved Thermal Comfort Model Leveraging Conditional Tabular GAN Focusing on Feature Selection
(2024)
The indoor thermal comfort in both homes and workplaces significantly influences the health and productivity of inhabitants. The heating system, controlled by Artificial Intelligence (AI), can automatically calibrate the indoor thermal condition by analyzing various physiological and environmental variables. To ensure a comfortable indoor environment, smart home systems can adjust parameters related to thermal comfort based on accurate predictions of inhabitants’ preferences. Modeling personal thermal comfort preferences poses two significant challenges: the inadequacy of data and its high dimensionality. An adequate amount of data is a prerequisite for training efficient machine learning (ML) models. Additionally, high-dimensional data tends to contain multiple irrelevant and noisy features, which might hinder ML models’ performance. To address these challenges, we propose a framework for predicting personal thermal comfort preferences, combining the conditional tabular generative adversarial network (CTGAN) with multiple feature selection techniques. We first address the data inadequacy challenge by applying CTGAN to generate synthetic data samples, incorporating challenges associated with multimodal distributions and categorical features. Then, multiple feature selection techniques are employed to identify the best possible sets of features. Experimental results based on a wide range of settings on a standard dataset demonstrated state-of-the-art performance in predicting personal thermal comfort preferences. The results also indicated that ML models trained on synthetic data achieved significantly better performance than models trained on real data. Overall, our method, combining CTGAN and feature selection techniques, outperformed existing known related work in thermal comfort prediction in terms of multiple evaluation metrics, including area under the curve (AUC), Cohen’s Kappa, and accuracy. Additionally, we presented a global, model-agnostic explanation of the thermal preference prediction system, providing an avenue for thermal comfort experiment designers to consciously select the data to be collected.
In intensively used agricultural landscapes, path margins are one of the few refuges and nurseries for wildlife. They provide e. g. food sources and overwintering opportunities for many insects, serve as migration corridors for animals, protect soil from erosion, increase its water-holding capacity, and increase soil organic carbon, contributing thus directly to biodiversity conservation and climate change mitigation. Path margins are often municipally owned but used and managed by agriculture. For a path margin to be functional, certain conditions must be fulfilled, such as the width, the botanical composition, and how it is managed through the seasons. Therefore, it must be managed under specific requirements. A multifunctional path margin can be achieved only through the commitment of all stakeholders (e.g., farmers, municipalities, conservationists, and civil society).
This study addresses the underrepresentation of women and the so-far neglected process perspective in empirical entrepreneurial research. It aims to identify the personality traits that differentiate successful female entrepreneurs from their less successful peers and to determine which traits are crucial for pre-launch, launch, and post-launch success. Independent t-tests on 305 female entrepreneurs (and 476 male entrepreneurs) from the DACH region highlight the role of self-efficacy, proactivity, locus of control, and need for achievement for female entrepreneurs. Multiple regression analyses further reveal the importance of self-efficacy for every phase of women’s entrepreneurial journey. While the need for autonomy was critical during pre-launch and launch, locus of control significantly predicted female entrepreneurial success in the pre-launch and post-launch phases. Contrary to previous research, risk-taking was not a crucial trait for female entrepreneurs when compared to their male counterparts, while both showed similar levels of need for autonomy, proactivity, need for achievement, perseverance, self-control, and locus of control. The study offers valuable insights into successful entrepreneurship and highlights the need for female- and phase-specific support programs to enhance self-efficacy among female entrepreneurs.
The decline of insect abundance and richness has been documented for decades and has received increased attention in recent years. In 2017, a study by Hallmann and colleagues on insect biomasses in German nature protected areas received a great deal of attention and provided the impetus for the creation of the project Diversity of Insects in Nature protected Areas (DINA). The aim of DINA was to investigate possible causes for the decline of insects in nature protected areas throughout Germany and to develop strategies for managing the problem.
A major issue for the protection of insects is the lack of insect-specific regulations for nature protected areas and the lack of a risk assessment and verification of the measures applied. Most nature protected areas border on or enclose agricultural land and are structured in a mosaic, resulting in an abundance of small and narrow areas. This leads to fragmentation or even loss of endangered habitats and thus threaten biodiversity. In addition, the impact of agricultural practices, especially pesticides and fertilisers, leads to the degradation of biodiversity at the boundaries of nature protected areas, reducing their effective size. All affected stakeholders need to be involved in solving these threats by working on joint solutions. Furthermore, agriculture in and around nature protected areas must act to promote biodiversity and utilise and develop methods that reverse the current trend. This also requires subsidies from the state to ensure economic sustainability and promote biodiversity-promoting practices.
Hochschulen und Gemeinden sind einem zunehmenden und permanenten Veränderungs- sowie Finanzierungsdruck ausgesetzt. Zudem haben Kommunen einen hohen Bedarf an Know-how, Kreativität, Innovationen, Personal sowie an Fachwissen in bestimmten Bereichen. Hochschulen auf der anderen Seite verfügen durch ihre WissenschaftlerInnen und Studierenden genau über diese Ressourcen. Vor diesem Hintergrund ist im Rahmen des BMBF-finanzierten Projekts „Innovative Hochschule“ ein Transfer-Kooperationsprojekt („Kommunale Innovationspartnerschaften“) zwischen der Hochschule Bonn-Rhein- Sieg und der Kommune Neunkirchen-Seelscheid, ca. 30 km östlich der Bundesstadt Bonn gelegen, durchgeführt worden. Die im Rahmen dieses Reallabors gewonnenen Erkenntnisse wurden im Format eines Toolkits zusammengefasst. Dies kann als Handlungsleitfaden auch für andere Hochschul-Kommune-Kooperationen verwendet werden. Eine Hochschul-Kommune-Kooperation stellt dabei eine projektbasierte Zusammenarbeit zwischen einer oder mehreren Hochschulen mit der politischen Vertretung einer oder mehrerer Kommunen sowie deren lokaler Wirtschaft und/oder Zivilgesellschaft dar.
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.