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Sowohl die offene als auch die verbandliche Kinder- und Jugendarbeit engagieren sich bereits seit rund 20 Jahren als Kooperationspartner von Ganztagsgrundschulen. Trotzdem scheint ihr Verhältnis zur Schule bis heute nicht grundsätzlich geklärt, was unter anderem daran ersichtlich wird, dass sich die Zusammenarbeit gleichzeitig in einer Annäherung an Schule und in einer Abgrenzung von ihr vollzieht. Angesichts dieses ambivalenten Verhältnisses und angesichts der Einführung des Rechtsanspruchs auf einen Ganztagsschulplatz ab dem Schuljahr 2026/2027 sowie dem dadurch steigenden Bedarf der Grundschulen an Kooperationspartnern, stellt sich (erneut) die Frage, inwieweit sich die Kinder- und Jugendarbeit im Ganztag einbringen sollte.
Previous research suggests that noise sensitivity is related to inefficient auditory processing that might increase the mental load of noise and affect noise evaluation. This assumption was tested in an experiment using a dual-task paradigm with a visual primary task and an auditory secondary task. Results showed that participants' noise sensitivity was positively correlated with mental effort. Furthermore, mental effort mediated the effect of noise sensitivity on loudness and unpleasantness ratings. The results thus support the idea that noise sensitivity is related to increased mental effort and difficulties in filtering auditory information and that situational factors should be considered.
Mass spectral libraries have proven to be essential for mass spectrum annotation, both for library matching and training new machine learning algorithms. A key step in training machine learning models is the availability of high-quality training data. Public libraries of mass spectrometry data that are open to user submission often suffer from limited metadata curation and harmonization. The resulting variability in data quality makes training of machine learning models challenging. Here we present a library cleaning pipeline designed for cleaning tandem mass spectrometry library data. The pipeline is designed with ease of use, flexibility, and reproducibility as leading principles.Scientific contributionThis pipeline will result in cleaner public mass spectral libraries that will improve library searching and the quality of machine-learning training datasets in mass spectrometry. This pipeline builds on previous work by adding new functionality for curating and correcting annotated libraries, by validating structure annotations. Due to the high quality of our software, the reproducibility, and improved logging, we think our new pipeline has the potential to become the standard in the field for cleaning tandem mass spectrometry libraries.
The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also, the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper, we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well-known MNIST data set based an handwritten digits.
With the increasing capabilities of machine learning systems and their potential use in safety-critical systems, ensuring high-quality data is becoming increasingly important. In this paper, we present a novel approach for the assurance of data quality. For this purpose, the mathematical basics are first discussed and the approach is presented using multiple examples. This results in the detection of data points with potentially harmful properties for the use in safety-critical systems.
Menschen mit Suchtverhalten, die Bürgergeld nach dem Sozialgesetzbuch II beziehen, zu ihren Wünschen an für sie hilfreiche Unterstützungsangebote zu befragen und aus ihren Schilderungen herauszuarbeiten, welche Bedeutung für sie Erwerbarbeit hat, fordert die Forschenden zu kritischen Selbstvergewisserungen heraus.Denn die qualitative Studie, die im Rahmen eines Modellprojekts, gefördert vom Bundesarbeitsministerium, durchgeführt wurde, berührt vier kritische Fachdebatten in der Sozialen Arbeit. Neben der (1) sozialpolitischen Aktivierungsprogrammatik sind hier v. a. die (2) Bezeichnung von Menschen mit Suchtverhalten sowie (3) methodologische Einwände gegen subjektorientierte Forschungsperspektiven und (4) Case Management bedeutsam. Nach der Positionierung in diesen Fachdebatten werden empirische Einblicke dazu gewährt, dass die Frage „Problembewältigung oder Erwerbsarbeit first?“ differenziert beantwortet wird.Ferner äußern die Bürgergeldbezieher:innen mit Suchtverhalten diverse Wünsche an die Unterstützung im Jobcenter und andere Hilfsangebote. Vor allem wünschen sie sich vom Jobcenter, dass es dort nicht nur um die Vermittlung in Erwerbsarbeit gehen sollte, sondern weitere und damit hybride Zielsetzungen verfolgt werden sollten.
The energy sector faces rapid decarbonisation and decision-makers demand reliable assessments of the security of electricity supply. For this, detailed simulation models with a high temporal and technological resolution are required. When confronted with increasing weather-dependent renewable energy generation, probabilistic simulation models have proven. The significant computational costs of calculating a scenario, however, limit the complexity of further analysis. Advances in code optimization as well as the use of computing clusters still lead to runtimes of up to eight hours per scenario. However ongoing research highlights that tailor-made approximations are potentially the key factor in further reducing computing time. Consequently, current research aims to provide a method for the rapid prediction of widely varying scenarios. In this work artificial neural networks (ANN) are trained and compared to approximate the system behavior of the probabilistic simulation model. To do so, information needs to be sampled from the probabilistic simulation in an efficient way. Because only a limited space in the whole design space of the 16 independent variables is of interest, a classification is developed. Finally it required only around 35 minutes to create the regression models, including sampling the design space, simulating the training data and training the ANNs. The resulting ANNs are able to predict all scenarios within the validity range of the regression model with a coefficient of determination of over 0.9998 for independent test data (1.051.200 data points). They need only a few milliseconds to predict one scenario, enabling in-depth analysis in a brief period of time.
In den Möglichkeiten der Anschlusskommunikation online liegt ein hohes Demokratisierungspotential der Gesellschaft. Durch die Beteiligung möglichst vieler Bürger am politischen Diskurs kann ein neuer inklusiver und vielstimmiger Kommunikationsraum geschaffen werden, in dem die pluralen, vielschichtigen Stimmen der Gesellschaft über die persönlichen Kommunikationsnetzwerke der Einzelnen hinaus in den Austausch treten und so Koorientierung ermöglicht wird. Doch in der Forschung gibt es unterschiedliche Deutungen, ob und inwieweit diese Potenziale eingelöst werden. Der vorliegende Beitrag analysiert basierend auf einer Onlinebefragung die Teilhabe an verschiedenen Formen der Anschlusskommunikation aus einer Milieuperspektive. Die Befunde zeigen, dass die Muster der Anschlusskommunikation sich mit den Ergebnissen der sonstigen Kommunikationspraktiken in den politisch-kommunikativen Milieus decken. Ein politisch selbstbewusstes, engagiertes und informiertes Milieu nutzt besonders die proaktiven Möglichkeiten der Anschlusskommunikation, um Meinungen zu debattieren und auszutauschen. Ein sich in der kommunikativen Teilhabe zurückhaltendes Milieu partizipiert in ebenso geringem Maße an der Anschlusskommunikation und koppelt sich so von einem integrierten Kommunikationsraum ab. Sich abschottende Milieus legen einen starken Fokus auf reaktive Formen der Anschlusskommunikation, die zur permanenten Affirmation eigener Ansichten genutzt werden. Diese unterschiedliche Nutzung trägt dazu bei, dass gesellschaftliche Spaltungstendenzen eher bestärkt statt reduziert werden.
This study aims to optimize the power generation of a conventional Manzanares solar chimney (SC) plant through strategic modifications to the collector inlet height, chimney diameter, and chimney divergence. Employing a finite volume-based solver for numerical analysis, we systematically scrutinize influential geometric parameters, including collector height (hi = 1.85 to 0.1 m), chimney inlet diameter (dch = 10.16 to 55.88 m), and chimney outlet diameter (do = 10.16 to 30.48 m). Our findings demonstrate that reducing the collector inlet height consistently leads to increased power output. The optimal collector inlet height of hi = 0.2 m results in a significant power increase from 51 to 117.42 kW (~ 2.3 times) without additional installation costs, accompanied by an efficiency of 0.25%. Conversely, enlarging the chimney diameter decreases the chimney base velocity and suction pressure. However, as turbine-driven power generation rises, the flow becomes stagnant beyond a chimney diameter of 45.72 m. At this point, power generation reaches 209 kW, nearly four times greater than the Manzanares plant, with an efficiency of 0.44%. Nevertheless, the cost of expanding the chimney diameter is substantial. Furthermore, the impact of chimney divergence is evident, with power generation, collector efficiency, overall efficiency, and collector inlet velocity all peaking at an outer chimney diameter of 15.24 m (corresponding to an area ratio of 2.25). At this configuration, power generation increases to 75.91 kW, approximately 1.5 times more than the initial design. Remarkably, at a low collector inlet height of 0.2 m, combining it with a chimney diameter of 4.5 times the chimney inlet diameter (4.5dch) results in an impressive power output of 635.02 kW, signifying a substantial 12.45-fold increase. To model the performance under these diverse conditions, an artificial neural network (ANN) is effectively utilized.
Counterpublics provide space for marginalised groups to voice opinions and experiences neglected by hegemonic discourse. This paper highlights publics that present themselves as counterpublics but which in actual fact reinforce existing hierarchies, particularly patriarchal structures. The case study of Girl Defined Ministries, a fundamentalist evangelical influencer duo based in Texas, links the research fields of digital religion and anti-feminist defensive publics, revealing parts of anti-feminism online that have hitherto been the reserve of digital religion studies. A consideration of the national history and religious developments of recent decades in the United States allows for a deeper understanding of this type of religious influencer. Girl Defined post content about their concept of “Biblical womanhood” on multiple platforms. In the present study, 56 blog articles by Girl Defined were analysed using qualitative content analysis through the analytical lens of the Social Identity model of Deindividuation Effects (SIDE), which reflects on how group identity is formed by simultaneously enhancing in-group and devaluing out-group norms. The findings demonstrate that Girl Defined portray the out-group, feminism, as an anti-God ideology responsible for the collective misery of women in Western societies, and hold women responsible for their own discontent by choosing the wrong path. Girl Defined therefore promote their in-group values, gender roles for women defined by God, and submission to men as the only way to live a joyful life. Presenting themselves as a persecuted and ostracised counterpublic to a feminist mainstream is central to Girl Defined’s argument. The paper adds to the existing literature on women anti-feminist and religious influencers as a development of mediatization.