University of Bamberg

Background Eating disorders (EDs) are increasingly prevalent in men, but men remain underrepresented across many ED-specific treatment settings. Based on the idea that persistent stereotypes, prejudice and discrimination, i.e., stigma against men with EDs, could impede help-seeking behaviors, the present study investigated whether stigma-related perceptions in men are associated with reduced help-seeking intentions for a broad range of disordered eating symptoms. Methods N = 132 adult men participated in a cross-sectional online survey and completed questionnaires on ED psychopathology, muscle dysmorphia, orthorexic eating, stigma-related perceptions of EDs in men, and help-seeking intentions. Results Moderator analyses showed that higher stigma-related perceptions were associated with reduced help-seeking intentions in response to increased ED symptom severity. However, this was only the case for traditionally “feminized” ED symptoms (related to thin-body ideals), but not for help-seeking with regard to muscularity-oriented, orthorexic, or avoidant/restrictive disordered eating. Conclusions Stigma may reduce help-seeking intentions with regard to “feminized” ED symptoms. The present findings suggest that perceptions of EDs as “women’s diseases” were associated with reduced help-seeking in men. Stigma towards men with EDs could thus be a possible barrier to help-seeking in men, highlighting the relevance of stigma-reducing interventions in clinical and community settings.

Background Experimental studies reveal that deficits in food‐related inhibitory control, rather than general impulsiveness, are closely linked to overweight and obesity. To date, the real‐world implications remain unknown, and it is unclear whether these results are supported in the clinical field. Objective To examine the effectiveness of a mobile health (mHealth) intervention with cognitive and behavioral therapeutic elements in altering impulsiveness and food‐related inhibitory control. Methods Prespecified secondary outcome analysis of a randomized controlled trial. Participants with overweight/obesity (BMI: M = 33.35 kg/m², SD = 3.79 kg/m², N = 213) were randomly assigned to either a 12‐week mHealth intervention (n = 116) or wait‐list control group (n = 97). The Barratt‐Impulsiveness‐Scale (BIS‐15) and the Food‐Related Inhibitory Control Scale (FRIS) were administered at baseline (T0) following the intervention (T1), at 9 and 15 month post baseline (T2, T3). Multi‐level analyses were calculated. Results Compared to the control group, the intervention group reported higher food‐related inhibitory control on several subscales of the FRIS: In Withholding in Social Situations at T1 (95% CI: 0.06–0.46) and T2 (95%CI: 0.09–0.50), Action Cancellation at T1 (95%CI: 0.05–0.45), Resisting despite Craving at T1 (95% CI: 0.07–0.49), Withstanding Rewarding Food at T2 (95%CI: 0.08–0.55) and Action Withholding at T3 (95% CI: 0.01–0.55). No differences were found for trait impulsiveness (T1: 95%CI: −1.91–0.47; T2: 95%CI: −1.65–0.84; T3: 95%CI: −0.88–1.67). Conclusions Food‐related inhibitory control, rather than global measures of impulsiveness, addresses the critical association between inhibitory control and health‐conscious dietary choices and can be improved by mHealth intervention. Trial Registration ClinicalTrials.gov identifier: NCT04080193

Robustness is a crucial requirement for the deployment of AI systems in real-world scenarios. In the context of AI planning, the concept of action reversibility, i.e., the ability to undo the effects of an action using a reverse plan, is a promising direction for achieving robust plans. Plans composed exclusively of reversible actions exhibit resilience against goal changes during the execution of the plan. However, the evaluation of action reversibility systems in STRIPS planning presents a challenge, given that standard planning benchmarks are often not suitable. Early experiments using a naive implementation of an action reversibility algorithm show that the available domain generation approach is susceptible to bias. Building on this existing domain generator, we introduce two slight variations that exhibit entirely different search space characteristics. We assess these domain generators using the naive action reversibility implementation and existing ASP implementations, and demonstrate that different generators indeed favor different implementations. As a follow-up to this line of research, we present a generalized domain generator facilitating the creation of domains with diverse search space characteristics. To finally reduce the utilization of contrived generation patterns, we propose another domain generator based on the Barabási-Albert model yielding less rigid domains. Our experiments demonstrate that these new domain generators can produce a variety of domains with diverse search space characteristics, enabling a less biased evaluation of action reversibility systems.

The paper presents methodology to generate experimental small area estimates (SAE) of poverty in four West African countries: Chad, Guinea, Mali, and Niger. Due to the absence of recent census data in the four countries, household level survey data are integrated with grid-level geospatial data, which are used as covariates in model-based estimation. Leveraging geospatial data enables reporting of poverty estimates more frequently at disaggregated administrative levels and makes estimation feasible in areas for which survey data are not available. The paper leverages the availability of a recent census in Burkina Faso for evaluation purposes. Estimates obtained with the same survey instruments and candidate geospatial covariates as the other four countries are compared against estimates obtained using recent census data and an empirical best predictor under a unit level model. For Burkina Faso, estimates obtained using geospatial data are highly correlated with the census-based ones in sampled areas but moderately correlated in non-sampled areas. The results demonstrate that in the absence of recent census data, small area estimation with publicly available geospatial covariates is feasible, can lead to large efficiency improvements compared to direct estimation, and improve the timeliness of small area estimates.

Purpose Deep convolutional neural networks (CNN) hold promise for assisting the interpretation of dopamine transporter (DAT)-SPECT. For improved communication of uncertainty to the user it is crucial to reliably discriminate certain from inconclusive cases that might be misclassified by strict application of a predefined decision threshold on the CNN output. This study tested two methods to incorporate existing label uncertainty during the training to improve the utility of the CNN sigmoid output for this task. Methods Three datasets were used retrospectively: a “development” dataset (n = 1740) for CNN training, validation and testing, two independent out-of-distribution datasets (n = 640, 645) for testing only. In the development dataset, binary classification based on visual inspection was performed carefully by three well-trained readers. A ResNet-18 architecture was trained for binary classification of DAT-SPECT using either a randomly selected vote (“random vote training”, RVT), the proportion of “reduced” votes ( “average vote training”, AVT) or the majority vote (MVT) across the three readers as reference standard. Balanced accuracy was computed separately for “inconclusive” sigmoid outputs (within a predefined interval around the 0.5 decision threshold) and for “certain” (non-inconclusive) sigmoid outputs. Results The proportion of “inconclusive” test cases that had to be accepted to achieve a given balanced accuracy in the “certain” test case was lower with RVT and AVT than with MVT in all datasets (e.g., 1.9% and 1.2% versus 2.8% for 98% balanced accuracy in “certain” test cases from the development dataset). In addition, RVT and AVT resulted in slightly higher balanced accuracy in all test cases independent of their certainty (97.3% and 97.5% versus 97.0% in the development dataset). Conclusion Making between-readers-discrepancy known to CNN during the training improves the utility of their sigmoid output to discriminate certain from inconclusive cases that might be misclassified by the CNN when the predefined decision threshold is strictly applied. This does not compromise on overall accuracy.

COVID-19 prevention measures and vaccine policies have led to substantial polarization across the world. I investigate whether and how vaccination status and vaccination status identification affect the sympathy and prejudice for vaccinated and unvaccinated individuals. Drawing on a preregistered vignette survey experiment in a large representative sample from Germany (n = 6,100) in December 2021, I show that prejudice was greater among the vaccinated towards the unvaccinated than vice versa. Furthermore, I find that differences in sympathy ratings are strongly subject to vaccination status identification. If individuals do not identify with their vaccination status, there are no differences in the evaluation of the in- and outgroups. Stronger vaccination status identification is, however, associated with greater prejudice among the vaccinated towards the unvaccinated but not for the unvaccinated towards the vaccinated. The results therefore show a stronger polarization on the side of the vaccinated that increases with the identification of one’s vaccination status.

In most industrialized countries, the choice of college majors is segregated by gender. Few students enroll in gender-atypical majors. Previous studies suggested that some attrition risks are associated with the gender composition of majors. In this paper, I investigated whether students in gender-atypical majors are more likely to leave the major by dropping out or switching to a different major with more same-sex students than those majoring in gender-typical subjects. Furthermore, I hypothesized that the relation between gender composition and non-completion risks is partially mediated by two social processes, namely poor social integration and disapproval of the major from parents and friends. Using data from undergraduate students from the German National Educational Panel Study, I conducted discrete-time survival analyses and a KHB decomposition. I found that both men and women in gender-atypical majors have a higher risk of switching to a major with a higher percentage of same-sex students than students in gender-typical majors. Women in gender-atypical majors also have a higher dropout risk. Poor social integration and disapproval of the major by parents and friends increase the switching risk and, in the case of social integration, also the dropout risk for all students. However, these two aspects cannot explain the higher attrition risk for students in gender-atypical majors, with one exception. Only for women in gender-atypical majors, lower approval of the major by friends partly mediates the association between the gender composition of the major and the risk of switching to a more female-dominated major.

Objective This study presents initial results from the KINMATRIX survey, a large‐scale source of ego‐centric network data offering an unprecedented level of scope and detail in mapping family relationships. Background Research on kinship networks is limited by the scarcity of available data. As a result, key phenomena remain insufficiently understood, including the importance of extended kin, contrasts between kinship lines, and cross‐national differences. Notably, extended kin provide a unique “strength in numbers” that can enhance social transmission, integration, and support. Method We analyzed data from anchor respondents aged 25–35 ( N = 11,788 anchors; 239,220 anchor‐kin dyads) collected in seven Western countries (Germany, Italy, Netherlands, Poland, Sweden, United Kingdom, and United States). Kinship networks included a large array of nuclear, extended, and complex kin (on average, 20 kin per anchor). We used descriptive methods to examine retrospective, current, and prospective assessments of kin ties across four measures: importance, closeness, contact, and support. Results We report three main findings: First, extended kin are central to younger adults' lives, representing at least half of the family members they are emotionally close to, regularly contact, and deem important. Second, kinship networks are matrilineally tilted. Maternal kin are emotionally closer, more frequently contacted, considered more important, and more supportive. Third, cross‐national comparisons reveal both similarities and notable differences, with the United States and Sweden showing elevated importance of extended and complex kin and Italy exhibiting higher social integration with nuclear and extended kin. Conclusion Data on kinship networks can significantly advance our understanding of key family phenomena.

Data security is becoming important as the amount of video data transmitted over the internet grows rapidly. This research article aims to maximize the security of transmitted video data by proposing a novel hybrid technique for video encryption and decryption. Elliptic Curve Cryptography (ECC) and the Modified Advanced Encryption Standard (MAES) are two encryption techniques that are included in the hybrid approach. By providing a more effective and safe method for video encryption and decryption, this research considerably advances the field of video data protection in Internet communication. In the proposed technique the video frames are extracted, and each frame is first encrypted using MAES technique and then again encrypted using ECC technique. After the encryption, the individual frames are merged to make an encrypted video. The same process is performed in reverse order to perform decryption of the video. The results of the experiments demonstrate the effectiveness of the suggested scheme: higher security, better accuracy, and shorter processing times when compared to well-known techniques such as Advanced Encryption Standard (AES), MAES, ECC, Simplified Data Encryption Standard (SDES), and Chaotic Map methods.

As the field of robotics evolves, robots become increasingly multi-functional and complex. Currently, there is a need for solutions that enhance flexibility and computational power without compromising real-time performance. The emergence of fog computing and cloud-native approaches addresses these challenges. In this paper, we integrate a microservicebased architecture with cloud-native fog robotics to investigate its performance in managing complex robotic systems and handling real-time tasks. Additionally, we apply model-based systems engineering (MBSE) to achieve automatic configuration of the architecture and to manage resource allocation efficiently. To demonstrate the feasibility and evaluate the performance of this architecture, we conduct comprehensive evaluations using both bare-metal and cloud setups, focusing particularly on realtime and machine-learning-based tasks. The experimental results indicate that a microservice-based cloud-native fog architecture offers a more stable computational environment compared to a bare-metal one, achieving over 20% reduction in the standard deviation for complex algorithms across both CPU and GPU. It delivers improved startup times, along with a 17% (wireless) and 23% (wired) faster average message transport time. Nonetheless, it exhibits a 37% slower execution time for simple CPU tasks and 3% for simple GPU tasks, though this impact is negligible in cloud-native environments where such tasks are typically deployed on bare-metal systems

In city centers worldwide, including the UNESCO World Heritage Site of Bamberg’s old town in Germany, alleviating pedestrian overcrowding is a pressing concern. Leveraging crowd-counting technologies with real-time data collection offers promising solutions, yet poses challenges regarding data privacy and informed consent. This preregistered study examines public response to a Smart City Bamberg project aimed at addressing pedestrian congestion through crowd-counting methods. We investigate informed consent by looking at understanding and acceptance of the project, as well as influencing factors, such as effectiveness of project explanation and trust. Through a three-stage study comprising exploratory interviews, a field study, and an online study, we reveal that the focus of project explanations significantly impacts understanding: Functional explanations, emphasizing project purpose, enhance comprehension compared to mechanistic explanations detailing project components. Additionally, project trust positively correlates with acceptance. Notably, understanding impacts acceptance through increased project trust. These findings underscore the importance of fostering understanding to garner public acceptance of crowd-counting projects. It is important, especially in the case of projects which aim to improve quality of life while also prioritizing robust data protection, that decisions regarding informed consent are grounded in comprehension rather than on preconceived biases against data sharing. Efforts should prioritize effective explanations to bolster project trust and consequently, promote acceptance.

This study analyses how changing positional advantages affected occupational returns for higher education in West Germany from 1974 to 2018. Positional advantages measure the advantages of educational levels relative to others during educational expansion. The impact of positional advantages on occupational returns plausibly differs regarding both the type of higher education degree and its level of occupational specificity. Using the German Microcensus and with the help of median regression models, the study tests if the socioeconomic status of Bachelor’s and Master’s graduates whose degrees have different levels of occupational specificity are systematically affected by the percentage of individuals with at least the same qualification at a given point in time. The empirical results reveal that higher education graduates benefit from educational expansion: positional advantages therefore affect occupational returns for different higher education degrees in divergent ways. Graduates with occupation-specific Master’s degrees appear to benefit most from educational expansion. Graduates with Bachelor’s degrees and less occupationally specific degrees benefit less from educational expansion. The empirical results suggest increasing positional competition within higher education. An eprint is available online: https://www.tandfonline.com/eprint/5CD8YW6MKCAQKTEHUYTF/full?target=10.1080/21568235.2024.2429079

Zusammenfassung Die Relationierung von Wissenschafts- und Berufsfeldbezug in der Lehrer:innenbildung hat nicht nur eine inhalts-, sondern auch eine personenbezogene Seite: In den meisten deutschen Bundesländern besteht formal das Schulpraxiserfordernis als zusätzliches Kriterium für die Berufung auf eine schulpädagogische Professur. Der Beitrag präsentiert vor diesem Hintergrund Ergebnisse einer Interviewstudie mit Schulpädagogikprofessor:innen, die über (keine) eigene(n) schulpraktische(n) Erfahrungen verfügen, und rekonstruiert vier Typen berufsbiografischer Identitätsarbeit: konservierend, kompensierend, transformierend und opponierend. Die eigene Berufsbiografie steht dabei im Dienst der selbstlegitimierenden Identitätsarbeit, wenngleich auch andere wahrgenommene Normen sich als bedeutsam zeigen. Die Ergebnisse werden vor dem Hintergrund disziplinpolitischer Diskurse diskutiert.

In recent times, the notion that inflation may be the result of conflicting claims by workers and capitalists over the distribution of income has experienced a revival in the academic and policy debate. Against this background, we investigate in this paper the macrodynamics of conflict inflation without and with the additional influence of the political sphere in an extended version of the baseline model of behavioral political cycles proposed by Galí (J Econ Behav Organ 212:50–67, 2023). By means of numerical simulations, we illustrate the reaction of main macroeconomic variables to the emergence of conflicting claims over the distribution of income between workers and capitalists, as well as their possible effects at the political sphere.