@article{KieflFischerSchmitt2024, author = {Kiefl, Sophia and Fischer, Sophie and Schmitt, Jan}, title = {Self-employed and stressed out? The impact of stress and stress management on entrepreneurs' mental health and performance}, series = {Frontiers in Psychology}, volume = {15}, journal = {Frontiers in Psychology}, publisher = {Frontiers Media SA}, issn = {1664-1078}, doi = {https://doi.org/10.3389/fpsyg.2024.1365489}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-55955}, year = {2024}, abstract = {Introduction: Entrepreneurs play a central role in economic and social stability, yet the start-up rate in Germany has declined in recent years, possibly due to the stress associated with entrepreneurial endeavors. Stressors such as financial uncertainty and time pressure are prevalent among entrepreneurs and negatively affect their psychological well-being. However, research on stress management strategies among self-employed individuals remains limited. Methods: This pilot study conducted a quantitative analysis with 117 self-employed participants in Germany. The study focused on typical entrepreneurial work demands and selected stress coping mechanisms. Results: The analysis revealed a significant correlation between quantitative demands and mental exhaustion. Furthermore, a high positive correlation between presenteeism and workload suggests that presenteeism may partially explain the variance in workload. These findings underscore how high job demands can lead to self-endangering behaviors that are detrimental to mental health. Discussion: Although no significant moderating effect of proactive coping on the relationship between job demands and mental exhaustion was observed, significant negative correlations between proactive coping and both job demands and mental exhaustion suggest a potential protective role of proactive coping against work-related stress. This study highlights the importance of understanding stress coping strategies among self-employed individuals and their impact on entrepreneurial success and mental well-being. Further research in this area is warranted to develop effective interventions to support the well-being and productivity of self-employed individuals in Germany.}, language = {en} } @article{KieflFischerSchmitt, author = {Kiefl, Sophia and Fischer, Sophie and Schmitt, Jan}, title = {Self-employed and stressed out? The impact of stress and stress management on entrepreneurs' mental health and performance}, series = {Frontiers in Psychology}, volume = {15}, journal = {Frontiers in Psychology}, publisher = {Frontiers}, doi = {10.3389/fpsyg.2024.1365489}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-56040}, pages = {15}, language = {en} } @article{WilhelmLotterScherdeletal., author = {Wilhelm, Markus and Lotter, Frank and Scherdel, Christian and Schmitt, Jan}, title = {Advancing Efficiency in Mineral Construction Materials Recycling: A Comprehensive Approach Integrating Machine Learning and X-ray Diffraction Analysis}, series = {buildings}, volume = {14}, journal = {buildings}, number = {2}, publisher = {MDPI}, doi = {10.3390/buildings14020341}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:863-opus-56030}, pages = {14}, abstract = {In the context of environmental protection, the construction industry plays a key role with significant CO2 emissions from mineral-based construction materials. Recycling these materials is crucial, but the presence of hazardous substances, i.e., in older building materials, complicates this effort. To be able to legally introduce substances into a circular economy, reliable predictions within minimal possible time are necessary. This work introduces a machine learning approach for detecting trace quantities (≥0.06 wt\%) of minerals, exemplified by siderite in calcium carbonate mixtures. The model, trained on 1680 X-ray powder diffraction datasets, provides dependable and fast predictions, eliminating the need for specialized expertise. While limitations exist in transferability to other mineral traces, the approach offers automation without expertise and a potential for real-world applications with minimal prediction time.}, language = {en} } @article{LangEngelmannSchiffleretal.2024, author = {Lang, Silvio and Engelmann, Bastian and Schiffler, Andreas and Schmitt, Jan}, title = {A simplified machine learning product carbon footprint evaluation tool}, series = {Cleaner Environmental Systems}, volume = {13}, journal = {Cleaner Environmental Systems}, publisher = {Elsevier BV}, issn = {2666-7894}, doi = {10.1016/j.cesys.2024.100187}, year = {2024}, abstract = {On the way to climate neutrality manufacturing companies need to assess the Carbon dioxide (CO2) emissions of their products as a basis for emission reduction measures. The evaluate this so-called Product Carbon Footprint (PCF) life cycle analysis as a comprehensive method is applicable, but means great effort and requires interdisciplinary knowledge. Nevertheless, assumptions must still be made to assess the entire supply chain. To lower these burdens and provide a digital tool to estimate the PCF with less input parameter and data, we make use of machine learning techniques and develop an editorial framework called MINDFUL. This contribution shows its realization by providing the software architecture, underlying CO2 factors, calculations and Machine Learning approach as well as the principles of its user experience. Our tool is validated within an industrial case study.}, language = {en} } @techreport{AsikainenEskolaSalinFischeretal., author = {Asikainen, Eveliina and Eskola-Salin, Nina and Fischer, Sophie and Giedraitien{\´e}, Vytautė and Beseckas, Povilas and Mairhofer, Stephanie and K{\"o}der, Lea and Schmitt, Jan and Walter, Holger and Guerrero-Perez, Olga and Bl{\´a}zquez-Parra, Elidia Beatriz and Bikuvien{\´e}, Ina and Lisina, Neringa and Tamulien{\´e}, Rasa and Liepinaitien{\´e}, Alina and M{\"a}kel{\"a}, Anne-Maria and Tahlo, Sanna and Selimaa, Hanna and Hager, Veronika and Ortega-Casanova, Joaquin and Mora-Segado, Patricia}, title = {Sustainability at HEIs: Mapping Good Practice}, doi = {10.57714/b75p-n548}, abstract = {Global climate change is a cognitive challenge for many people and often evokes negative associations due to its complexity and interactions with politics, social movements and economic developments. Therefore, the possession of green skills becomes central to the fight against climate change. The European Council conclusions recognize this urgency and underline the need for a transition to green skills. This recognition also extends to higher education, where institutions have a crucial role to play in tackling the climate crisis. Personal Green Skills in Higher Education (PeGSinHE) is an Erasmus+ KA2 project coordinated by Kauno Kolegija (KK, Lithuania), Tampere University of Applied Sciences (TAMK, Finland), Hochschule f{\"u}r Agrar- und Umweltp{\"a}dagogik (HAUP, Austria), Universidad de M{\´a}laga (UMA, Spain) and Technical University of Applied Sciences W{\"u}rzburg Schweinfurt (THWS, Germany). The strategically designed project aims not only to promote green skills among students and encourage personal behavioral change in line with the Sustainable Development Goals, but also to instill a sense of social responsibility in the partner institutions. The focus is on empowering lecturers at partner universities through innovative teaching and learning methods to effectively impart green skills to students. This report describes the objectives and methodology used to assess environmental and sustainability competencies in the higher education institutions involved in the project. Methodologically, the report uses an assessment template designed to provide a comprehensive overview of best practice and baseline levels of environmental and sustainability competencies. It advocates the involvement of key stakeholders from all five partner Higher Education Institutions to ensure a broad perspective on these practices and competences within their respective countries and organizations. Different methods and perspectives will be used to collect data to enable a holistic understanding of the topic. The joint completion of the assessment template serves as a catalyst for joint discussions on the level of environmental and sustainability competencies and the identification of best practices in each organization. The results show that national implementation strategies are relatively loose, although some competency descriptions set targets for undergraduate degree programs. Challenges faced by higher education staff include resource constraints, particularly lack of time, the need for a deeper understanding of sustainable development and pedagogical tools, and the need for improved opportunities for collaboration. Given the time and resource constraints of this study, the results must be considered preliminary. Nevertheless, they confirm the findings of previous studies.}, language = {en} }