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Klimaschutz zwischen Polarisierung und Protest: Öffentliche Meinung und die Rolle konkreter Maßnahmen
Get PDF80 Prozent der Menschen in Deutschland machen sich Sorgen über den Klimawandel (Gagné/Krause 2021). Selbst unter dem Eindruck des russischen Angriffskriegs gegen die Ukraine und dessen Folgen rangiert der Klimawandel unter den drei wichtigsten Problemen, denen sich Deutschland gegenwärtig gegenübersieht (Statista). 71 Prozent der efragten in der FES-Studie „Vertrauensfrage Klimaschutz“ stimmen der Aussage zu, dass die Politik für die Einhaltung von beschlossenen Klimaschutzzielen sorgen muss (Hagemeyer et al. 2024). Folgt aus diesen Zahlen, dass die Menschen auch Maßnahmen für mehr Klimaschutz unterstützen? Die repräsentative Umfrage und das Experiment, die wir im Dezember 2023 mit 4.400 deutschen Wähler:innen durchgeführt haben, legen vier Einsichten nahe:
• Die Unterstützung konkreter Klimaschutzmaßnahmen ist insgesamt verhalten und unterscheidet sich sehr stark zwischen den verschiedenen Maßnahmen. Höhere Unterstützung ist oft mit einer stärkeren Polarisierung zwischen Befürworter:innen und Gegner:innen verbunden.
• Die Unterstützung variiert mit dem Politiktyp. Regulative Klimaschutzmaßnahmen erhalten am meisten Zuspruch. Steuerpolitische Maßnahmen mobilisieren den stärksten Widerspruch.
• Die Unterstützung hängt stark von der politischen Lagerzugehörigkeit ab, mit konsistent größerer Zustimmung links der Mitte. Lagerübergreifende Koalitionen für klimapolitische Maßnahmen sind mit der derzeitigen öffentlichen Meinung schwer zu schmieden.
• Die Unterstützung wird von der Art und Intensität von Klimaprotesten beeinflusst. Insgesamt reduziert Protest eher die Zustimmung zu Klimaschutzmaßnahmen. Radikale Protestformen wie das Klimakleben rufen besonders starken Widerstand hervor
The EU–UK Trade and Cooperation Agreement Passenger Name Records Provisions: Framing the Effectiveness of Degrees of Legalisation and Institutionalisation
Get PDFThis chapter explores descriptively the recent evolution of PNR law in EU external relations law, evolving into a trade agreement, with a plethora of new actors and 83oversight provisions through the framing of this evolution as degrees of legalisation and institutionalisation. Oversight is a key means to examine these developments, as one of the most important legal issues arising in EU law for PNRs in this period. It considers legalisation in section II, situating PNRs as an evolution of the AFSJ through law initially, moving now in the TCA into a trade agreement. Section III, on institutionalisation, sets out the many actors involved in PNRs oversight, and section IV discusses the early outcomes of that oversight, which appear to indicate unimpressive effectiveness, despite the many layers of governance (which are also non-transparent and difficult to decipher). The chapter concludes, in section V, that PNRs law generally appears to have many shortcomings that are not easily remedied or ameliorated by the TCA, however significant their presence there might b
Neuroticism Is Linked With Liberal Ideology in Young, but not Old, People in the United States
Get PDFPolarization in the United States is partly due to a remarkable ideological divide between generations. Although substantial research has investigated why old people have become more conservative, less is known about why young people have become more liberal. The article investigates this by probing the role of neuroticism. It hypothesises that, compared to older cohorts, younger ones have grown up during a more competitive historical period that has led many to become more neurotic and, in turn, to support the left. This predicts that, in the United States, neuroticism is linked with liberal ideology in young, but not old, people. This prediction is supported in two studies. A third study found no such effect outside the United States, suggesting that the effect observed in the United States is not due to aging but to generational experiences. Overall, these findings highlight a potential role for neuroticism in explaining why young Americans have become more liberal
Research Brief: Mismatches between UK food supply and dietary guidelines – a dietary gap assessment
Get PDFToo good to waste! Short-term and long-term effects of a leftover meals intervention program on household dinner food waste reduction
Get PDFHousehold food waste is a global concern impacting the environment, society, and economy. Effective intervention strategies are needed towards households with children due to their high reported dinner food waste. This study investigates the short-term and long-term impact of a behavioural intervention on dinner food waste in households with children, discussing the behaviour-change mechanisms in light of the Comprehensive Action Determination Model framework. A randomised controlled trial was conducted with 230 Norwegian families that involved incorporating leftovers into dinners and using online learning resources for 4 weeks (intervention group). Additionally, the participants monitored their dinner food waste for 7 weeks (intervention and control groups). Short-term, both groups reduced their total waste, but the reduction was more significant in the intervention group (n = 113) than the control group (n = 117), with −39 % against −22 % in the control group. Both groups discarded less fresh fruit, bread and dairy products. The intervention group additionally discarded lower amounts of fresh vegetables, potato products and pasta. Long-term, at 52 weeks follow-up (n = 144), the difference in reduction between the groups was no longer significant. However, both groups had reduced their total food waste, indicating the sustained impact of increased awareness regarding household waste, also from mere self-reporting. Globally, the participating households reduced their dinner food waste by −29 % at week 52, equivalent to −146 g/week. These results suggest that food waste organisations and policymakers should consider combining practical and informational strategies for effective short-term waste reduction results, and highlight self-reporting as a valuable tool for triggering long-term behavioural change
Attention-Enhanced Progressive Transfer Learning for Scalable Seismic Vulnerability Assessment of RC Frame Buildings
Get PDFUrban infrastructure in seismic zones demands efficient and scalable tools for damage prediction. This study introduces an attention-integrated progressive transfer learning (PTL) framework for the seismic vulnerability assessment (SVA) of reinforced concrete (RC) frame buildings. Traditional simulation-based vulnerability models are computationally expensive and dataset-specific, limiting their adaptability. To address this, we leverage a pretrained artificial neural network (ANN) model based on nonlinear static pushover analysis (NSPA) and Monte Carlo simulations for a 4-story RC frame, and extended its applicability to 2-, 8-, and 12-story configurations via PTL. An attention mechanism is incorporated to prioritize critical features, enhancing interpretability and classification accuracy. The model achieves 95.64% accuracy across five damage categories and an R2 of 0.98 for regression-based damage index predictions. Comparative evaluation against classical and deep learning models demonstrates superior generalization and computational efficiency. The proposed framework reduced retraining requirements across varying building heights, shows potential adaptability to other structural typologies, and maintains high predictive fidelity, making it a practical AI solution for structural risk evaluation in seismically active regions
A dynamic quantum-resistant code-based public key encryption scheme
No full textCode-based post-quantum cryptography is seeing an unprecedented growth due to its significance in addressing the security threats posed by quantum computers toward digital communication, leveraging its strength from the well-known hard problems of coding theory. Code-based cryptosystems are vulnerable to attacks that exploit the inherent structure of the underlying code, compromising security in many cases. Although McEliece cryptosystem with Goppa codes provide substantial resistance, this comes at the cost of huge key sizes, limiting their practicality. The proposed work, dynamic code-based McEliece cryptosystem, introduces the notion of dynamicity to the code-based cryptosystem and intensifies the random nature necessary to overcome the attacks. Unlike the conventional schemes that rely on a fixed underlying code and its generator matrix, our approach dynamically changes the code structure in response to trigger events to create cipher keys. This dynamic code transformation preserves the core efficiency of the cipher while significantly improving security against structural attacks, decoding attacks and side channel analysis. The proposed scheme retains IND-CPA security under standard assumptions while also rendering chosen ciphertext attacks significantly challenging. Our work establishes a new direction for enhancing the security of code-based encryption in practical applications
MacroVAE: Counterfactual Financial Scenario Generation via Macroeconomic Conditioning
Get PDFHow would a portfolio perform under alternative macroeconomic conditions? Traditional scenario analysis in finance relies heavily on historical data, thus limiting risk assessment under rare or unobserved macroeconomic environments. We introduce MacroVAE, a variational autoencoder that generates realistic return sequences based on macroeconomic indicators to enable counterfactual scenario analysis. Trained on historical futures returns and macroeconomic data from global economies, MacroVAE generates return sequences conditioned on specified macroeconomic scenarios. The model uses convolutional ResNet blocks with Feature-wise Linear Modulation for stable macroeconomics-driven generation. In rolling out-of-sample evaluation, MacroVAE outperforms state-of-the-art generative baselines in replicating empirical distributions and financial stylized facts. We demonstrate two applications: counterfactual scenario analysis under alternative macroeconomic conditions, and forward-looking stress testing across diverse inflation-growth combinations, including ones rarely or not observed historically. MacroVAE enables systematic exploration of macroeconomic conditions, expanding the toolkit for portfolio risk management
A Calogero Model with root string representatives of infinite order Coxeter orbits
Get PDFWe present a worked example for the new extensions of the multi-particle Calogero model endowed with infiniteWeyl group symmetry of affine and hyperbolic type. Building upon the hyperbolic extension of the A3-Kac-Moody algebra, we construct an explicit realisation of the model in terms of infinite root systems generated from Coxeter orbits. To address the challenge of summing over infinitely many roots, we introduce root string representatives that span the invariant root space while preserving invariance under the affine Weyl group. This approach yields closed-form expressions for the potentials, which by construction are invariant under the full affine Weyl symmetry. Moreover, we demonstrate that in an appropriate infinite-coordinate limit the model reduces smoothly to the conventional four particle A3-Calogero system. Our construction constitutes a systematic method for implementing infinite-dimensional symmetries into Calogero-type models, thus broadening their algebraic and physical applicability
Gaze-Aware Visualisation: Design Considerations and Research Agenda
Get PDFEye tracking provides a unique perspective on the inherently visual discourse between visualization systems and their users, and has recently become sufficiently precise and affordable to be integrated as regular input into workstations and virtual or augmented reality headsets alike. As such, real-time eye tracking can now contribute significantly toward the development of gaze-aware visualizations that infer and monitor users’ needs to actively support their activities. To facilitate such systems we make three contributions. First, we structure and discuss design considerations for gaze-aware visualizations along four axes: measurable data; inferable data; opportunities for support; and limiting factors to beware. Second, we distill visualization research challenges that preclude such systems. Finally, we show via three usage scenarios how to apply these design considerations to imagine how existing systems can benefit from real-time eye tracking. We combined a structured literature analysis, a consideration of suitable places for eye-tracking integration in the typical visualization ecosystem, and design space modeling. Eye tracking has significant potential to improve the interactive visual analysis of data across many visualization domains. Our paper attempts to provide a comprehensive, general survey and conceptual discussion in this promising field, outlining the state-of-the-art and future research opportunitie
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