Geschlechtsrollen-Selbstkonzept, Gesundheit und gesundheitsrelevantes Handeln

Im Rahmen der Untersuchung wird die Bedeutung des Geschlechtsrollen-Selbstkonzepts (G-SK), d. h. der Identifikation mit gesellschaftlichen Geschlechterstereotypen und -rollen, für die Ausübung körperlicher Aktivität und das Essverhalten sowie gesundheitsbezogene Selbsteinschätzungen im Sinne des Gesundheits-Selbstkonzepts untersucht. Es wird eruiert, ob das G-SK in Bezug auf die Merkmals-ausprägung gar eine höhere Relevanz besitzt als das Geschlecht

Stress: Personal matter or family affair? Intra- and inter-individual relationships between stress, physical activity, sedentery behavior, and nutrition

Individual health behavior, which is determined by individual motives, emotions, and cognitive processes, is embedded in a social environment. One of the most important social environments is the family. According to Family Reciprocal Determinism, stress perceived by one family member becomes part of the family environment and may affect interactions within the family, as well as the health behavior of all family members. This study investigated 214 families, each represented by a mother, a father, and one of their children. The aim of the study was to examine intra- and inter-individual relationships between perceived stress and three health behaviors: physical activity, leisure-time sedentary behavior, and food consumption. The results indicate that individually perceived stress is related to individual health behavior as well as the health behavior of other family members. However, these relationships vary among family members. The inter-individual analyses revealed that this effect is strongest for the relationship of mothers’ stress to other family members’ health behavior. Investigating the link between perceived stress and health behavior from a family perspective may be useful for understanding the relationship between stress and health

Language endangerment and language documentation in Africa

Non peer reviewe

Das Konstanzer BA/MA-Modell im Studiengang Lehramt Gymnasium

Im Dezember 2013 beschloss der Ministerrat von Baden-Württemberg die Eckpunkte zur Reform der Ausbildung von Lehrer/-innen an den Universitäten und Hochschulen des Landes. Zentraler Punkt des Beschlusses war die Umstellung der Lehramtsstudiengänge vom zwar modularisierten, zeitlich aber kohärenten Staatsexamensstudiengang auf die zweistufi ge Bachelor- und Masterstruktur (BA/MA) zum Wintersemester 2015/16 an den lehrerbildenden Universitäten und Hochschulen des Landes. Die Umstrukturierung sollte es unter anderem ermöglichen, dass die Studierenden sich erst dann verbindlich für den Beruf der Lehrerin/des Lehrers entscheiden müssen, „nachdem sie im Bachelor bereits Erfahrungen gesammelt haben. Bis dahin bleibe die Möglichkeit offen, sich auch anderen Studiengängen zuzuwenden“, wie die Wissenschaftsministerin des Landes in einer Pressemitteilung betonte.publishe

Stress: Personal matter or family affair? : Intra- and inter-individual relationships between stress, physical activity, sedentary behavior and nutrition

Individual health behavior, which is determined by individual motives, emotions, and cognitive processes, is embedded in a social environment. One of the most important social environments is the family. According to Family Reciprocal Determinism, stress perceived by one family member becomes part of the family environment and may affect interactions within the family, as well as the health behavior of all family members. This study investigated 214 families, each represented by a mother, a father, and one of their children. The aim of the study was to examine intra- and inter-individual relationships between perceived stress and three health behaviors: physical activity, leisure-time sedentary behavior, and food consumption. The results indicate that individually perceived stress is related to individual health behavior as well as the health behavior of other family members. However, these relationships vary among family members. The inter-individual analyses revealed that this effect is strongest for the relationship of mothers’ stress to other family members’ health behavior. Investigating the link between perceived stress and health behavior from a family perspective may be useful for understanding the relationship between stress and health.publishe

RID—Roof Information Dataset for Computer Vision-Based Photovoltaic Potential Assessment

Computer vision has great potential to accelerate the global scale of photovoltaic potential analysis by extracting detailed roof information from high-resolution aerial images, but the lack of existing deep learning datasets is a major barrier. Therefore, we present the Roof Information Dataset for semantic segmentation of roof segments and roof superstructures. We assessed the label quality of initial roof superstructure annotations by conducting an annotation experiment and identified annotator agreements of 0.15–0.70 mean intersection over union, depending on the class. We discuss associated the implications on the training and evaluation of two convolutional neural networks and found that the quality of the prediction behaved similarly to the annotator agreement for most classes. The class photovoltaic module was predicted to be best with a class-specific mean intersection over union of 0.69. By providing the datasets in initial and reviewed versions, we promote a data-centric approach for the semantic segmentation of roof information. Finally, we conducted a photovoltaic potential analysis case study and demonstrated the high impact of roof superstructures as well as the viability of the computer vision approach to increase accuracy. While this paper’s primary use case was roof information extraction for photovoltaic potential analysis, its implications can be transferred to other computer vision applications in remote sensing and beyond

Towards Scalable Economic Photovoltaic Potential Analysis Using Aerial Images and Deep Learning

Roof-mounted photovoltaic systems play a critical role in the global transition to renewable energy generation. An analysis of roof photovoltaic potential is an important tool for supporting decision-making and for accelerating new installations. State of the art uses 3D data to conduct potential analyses with high spatial resolution, limiting the study area to places with available 3D data. Recent advances in deep learning allow the required roof information from aerial images to be extracted. Furthermore, most publications consider the technical photovoltaic potential, and only a few publications determine the photovoltaic economic potential. Therefore, this paper extends state of the art by proposing and applying a methodology for scalable economic photovoltaic potential analysis using aerial images and deep learning. Two convolutional neural networks are trained for semantic segmentation of roof segments and superstructures and achieve an Intersection over Union values of 0.84 and 0.64, respectively. We calculated the internal rate of return of each roof segment for 71 buildings in a small study area. A comparison of this paper’s methodology with a 3D-based analysis discusses its benefits and disadvantages. The proposed methodology uses only publicly available data and is potentially scalable to the global level. However, this poses a variety of research challenges and opportunities, which are summarized with a focus on the application of deep learning, economic photovoltaic potential analysis, and energy system analysis