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We tested whether a brief self-affirmation writing intervention protected against identity-threats (i.e., stereotyping and discrimination) for adolescents' school-related adjustment. The longitudinal study followed 639 adolescents in Germany (65% of immigrant descent, 50% female, M-age = 12.35 years, SDage = .69) from 7(th) grade (pre-intervention at T1, five to six months post-intervention at T2) to the end of 8(th) grade (one-year follow-up at T3). We tested for direct and moderated (by heritage group, discrimination, classroom cultural diversity climate) effects using regression and latent change models. The self-affirmation intervention did not promote grades or math competence. However, in the short-term and for adolescents of immigrant descent, the intervention prevented a downward trajectory in mastery reactions to academic challenges for those experiencing greater discrimination. Further, it protected against a decline in behavioral school engagement for those in positive classroom cultural diversity climates. In the long-term and for all adolescents, the intervention lessened an upward trajectory in disruptive behavior. Overall, the self-affirmation intervention benefited some aspects of school-related adjustment for adolescents of immigrant and non-immigrant descent. The intervention context is important, with classroom cultural diversity climate acting as a psychological affordance enhancing affirmation effects. Our study supports the ongoing call for theorizing and empirically testing student and context heterogeneity to better understand for whom and under which conditions this intervention may work.
Local laws on urban policy, i.e., ordinances directly affect our daily life in various ways (health, business etc.), yet in practice, for many citizens they remain impervious and complex. This article focuses on an approach to make urban policy more accessible and comprehensible to the general public and to government officials, while also addressing pertinent social media postings. Due to the intricacies of the natural language, ranging from complex legalese in ordinances to informal lingo in tweets, it is practical to harness human judgment here. To this end, we mine ordinances and tweets via reasoning based on commonsense knowledge so as to better account for pragmatics and semantics in the text. Ours is pioneering work in ordinance mining, and thus there is no prior labeled training data available for learning. This gap is filled by commonsense knowledge, a prudent choice in situations involving a lack of adequate training data. The ordinance mining can be beneficial to the public in fathoming policies and to officials in assessing policy effectiveness based on public reactions. This work contributes to smart governance, leveraging transparency in governing processes via public involvement. We focus significantly on ordinances contributing to smart cities, hence an important goal is to assess how well an urban region heads towards a smart city as per its policies mapping with smart city characteristics, and the corresponding public satisfaction.
FicucariconeD (1) and its 4 '-demethyl congener 2 are isoflavones isolated from fruits of Ficus carica that share a 5,7-dimethoxy-6-prenyl-substituted A-ring. Both naturalproducts were, for the first time, obtained by chemical synthesisin six steps, starting from 2,4,6-trihydroxyacetophenone. Key stepsare a microwave-promoted tandem sequence of Claisen- and Cope-rearrangementsto install the 6-prenyl substituent and a Suzuki-Miyaura crosscoupling for installing the B-ring. By using various boronic acids,non-natural analogues become conveniently available. All compoundswere tested for cytotoxicity against drug-sensitive and drug-resistanthuman leukemia cell lines, but were found to be inactive. The compoundswere also tested for antimicrobial activities against a panel of eightGram-negative and two Gram-positive bacterial strains. Addition ofthe efflux pump inhibitor phenylalanine-arginine-beta-naphthylamide(PA beta N) significantly improved the antibiotic activity in mostcases, with MIC values as low as 2.5 mu M and activity improvementfactors as high as 128-fold.
Introduction:
Decision making results not only from logical analyses, but seems to be further guided by the ability to perceive somatic information (interoceptive accuracy). Relations between interoceptive accuracy and decision making have been exclusively studied in adults and with regard to complex, uncertain situations (as measured by the Iowa Gambling Task, IGT).
Methods:
In the present study, 1454 children (6-11 years) were examined at two time points (approximately 1 year apart) using an IGT as well as a delay-of-gratification task for sweets-items and toy-items. Interoceptive accuracy was measured using a child-adapted version of the Heartbeat Perception Task.
Results:
The present results revealed that children with higher, as compared to lower, interoceptive accuracy showed more advantageous choices in the IGT and delayed more sweets-items, but not toy-items, in a delay-of-gratification task at time point 2 but not at time point 1. However, no longitudinal relation between interoceptive accuracy and decision making 1 year later could be shown.
Discussion:
Results indicate that interoceptive accuracy relates to decision-making abilities in situations of varying complexity already in middle childhood, and that this link might consolidate across the examined 1-year period. Furthermore, the association of interoceptive accuracy and the delay of sweets-items might have implications for the regulation of body weight at a later age.
Weathering the storm?
(2023)
Democratization scholars are currently debating if we are indeed witnessing a third wave of autocratization. While this has led to an extensive debate about the future of the liberal international order, we still know relatively little about the consequences of autocratization for international organizations (IOs). In this article, we explore to what extent autocratization has led to changes in the composition of IO membership. We propose three different ways of conceptualizing autocratization of IO membership. We argue that we should move away from a dichotomous understanding of regime type and regime change, but rather focus on composition of subregime types to understand current developments. We build on updated membership data for 73 IOs through 2020 to map membership configurations based on the V-Dem Electoral Democracy Index. Contrary to current debates on the crisis of the liberal order, we find that many IOs are not (yet) affected by broad autocratization of their membership that would endanger democratic majorities or overall democratic densities. However, we also observe the disappearance of formerly homogenous democratic clubs due to democratic backsliding in a number of European and Latin American IO member states, as well as a return of autocratic clubs in Southeast Asia and Southern Africa. These findings have important implications for the broader research agenda on international democracy promotion and human right protection as well as the study of legitimacy and the effectiveness of international organizations.
The analysis of event time series is in general challenging. Most time series analysis tools are limited for the analysis of this kind of data. Recurrence analysis, a powerful concept from nonlinear time series analysis, provides several opportunities to work with event data and even for the most challenging task of comparing event time series with continuous time series. Here, the basic concept is introduced, the challenges are discussed, and the future perspectives are summarized.
International institutions are an essential driving force of contemporary policies to combat gender-based violence but remain toothless if political actors do not implement them in domestic policies. How can scholars conceptualise the transposition of international gender-based violence norms into domestic policies? I argue that discourse network analysis provides a powerful conceptual and methodological extension of critical frame analysis to understand how frames shape the meaning of gender-based violence norms in multi-level institutional contexts. Frames’ normative and cognitive network structure invites combining discourse network and frame analysis techniques that locate frames’ power in their ability to connect different institutional spheres temporally and spatially. I outline a multi-level research agenda that traces the framing processes of international norms and their domestic implementation through gender-based violence policies in the Council of Europe’s Istanbul Convention. This agenda includes avenues to study how complex transnational policy frameworks like the Istanbul Convention play out in domestic policy implementation.
About 15 years ago, the first Massive Open Online Courses (MOOCs) appeared and revolutionized online education with more interactive and engaging course designs. Yet, keeping learners motivated and ensuring high satisfaction is one of the challenges today's course designers face. Therefore, many MOOC providers employed gamification elements that only boost extrinsic motivation briefly and are limited to platform support. In this article, we introduce and evaluate a gameful learning design we used in several iterations on computer science education courses. For each of the courses on the fundamentals of the Java programming language, we developed a self-contained, continuous story that accompanies learners through their learning journey and helps visualize key concepts. Furthermore, we share our approach to creating the surrounding story in our MOOCs and provide a guideline for educators to develop their own stories. Our data and the long-term evaluation spanning over four Java courses between 2017 and 2021 indicates the openness of learners toward storified programming courses in general and highlights those elements that had the highest impact. While only a few learners did not like the story at all, most learners consumed the additional story elements we provided. However, learners' interest in influencing the story through majority voting was negligible and did not show a considerable positive impact, so we continued with a fixed story instead. We did not find evidence that learners just participated in the narrative because they worked on all materials. Instead, for 10-16% of learners, the story was their main course motivation. We also investigated differences in the presentation format and concluded that several longer audio-book style videos were most preferred by learners in comparison to animated videos or different textual formats. Surprisingly, the availability of a coherent story embedding examples and providing a context for the practical programming exercises also led to a slightly higher ranking in the perceived quality of the learning material (by 4%). With our research in the context of storified MOOCs, we advance gameful learning designs, foster learner engagement and satisfaction in online courses, and help educators ease knowledge transfer for their learners.
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.