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Nuclear energy is a contested topic, requiring trade-offs in energy independence, ethicality and uncertainty. Anthropogenic climate change complicates these decisions further, with nuclear energy competing with other low-carbon and sustainable energy sources. Decisions about nuclear energy’s role, as part of a sustainable energy system, must be made in cooperation with all stakeholders. However, it is unclear how the public is involved in these decisions in the UK. This study aims to address this gap, exploring the degree to which public participation has occurred in the UK.

This paper conducted a scoping review of public participation in UK nuclear energy decision-making in the context of sustainable energy transitions, where the government retains and promotes nuclear energy as part of a sustainable energy system. Following a systematic literary search, this paper reviewed 28 academic and grey literature documents.

Public participation has primarily been conducted as consultations rather than active participation. There is limited evidence that consultations have meaningfully contributed to politically and socially responsible (i.e. individuals and groups working together for community benefit) decision-making, with public opinion on nuclear energy’s role being divided and is influenced by how it is framed.

Social aspects of nuclear energy development have historically received less attention than environmental and economic elements; the role of engagement and participation is relatively rare. Modern literature reviews in this context are largely absent, a gap this paper originally contribute to. This paper suggest ways in which how effective, inclusive engagement process could contribute to a fairer, responsible decision-making process and energy system in the UK.

This chapter explores the nature of military law and IHL during the cold war period. It explores what treaties were completed, Additional Protocols I and II of the 1949 Geneva Conventions, the ad hoc international tribunals of the 1990s and 2000s, and examines the ICJ’s ruling of the legality of nuclear weapons.

Thin cracks on the surface, such as those found in nuclear power plant concrete structures, are difficult to identify because they tend to be thin. This paper aims to design a novel segmentation network, called U-shaped contextual aggregation network (UCAN), for better recognition of weak cracks.

UCAN uses dilated convolutional layers with exponentially changing dilation rates to extract additional contextual features of thin cracks while preserving resolution. Furthermore, this paper has developed a topology-based loss function, called ℓ_cl Dice, which enhances the crack segmentation’s connectivity.

This paper generated five data sets with varying crack widths to evaluate the performance of multiple algorithms. The results show that the UCAN network proposed in this study achieves the highest F1-Score on thinner cracks. Additionally, training the UCAN network with the ℓ_cl Dice improves the F1-Scores compared to using the cross-entropy function alone. These findings demonstrate the effectiveness of the UCAN network and the value of incorporating the ℓ_cl Dice in crack segmentation tasks.

In this paper, an exponentially dilated convolutional layer is constructed to replace the commonly used pooling layer to improve the model receptive field. To address the challenge of preserving fracture connectivity segmentation, this paper introduces ℓ_cl Dice. This design enables UCAN to extract more contextual features while maintaining resolution, thus improving the crack segmentation performance. The proposed method is evaluated using extensive experiments where the results demonstrate the effectiveness of the algorithm.

Dark (Netflix, 2017–2020) is a German-produced science fiction television series, created by Baran bo Odar and Jantje Friese. Set in the geographically ambiguous small town of Winden, Dark is an intricate time-travel saga primarily across different epochs. With its emphasis on uncanny natural settings and fairy tale tropes (such as lost children, mysterious travelers, magical devices, etc.), Dark can easily be interpreted as fairy tale. Central is young Jonas Kahnwald who loses his father and witnesses the mysterious disappearance of a local boy. These traumas lead to shocking truths about his heritage. Jonas is the hero (both victim and seeker, after Propp's definition) though his twisting quest brings him face-to-face with two older versions of himself: The middle-aged Jonas fulfils a mentor/donor role for the younger but is conflicted in his desires to both perpetuate and unpick ‘the knot’. Later, Jonas encounters cataclysmic extremist ‘Adam’, a mature version of himself who acts as antagonist. Thusly, Dark centres White male trauma, agency, and ego to reflect responses to historic cultural trauma (such as the notion of the ‘anti-Heimat’) whilst also critiquing traditional conceptions of masculinity through young Jonas's actions. This chapter maps the interplay and representation of ego and trauma. Through textual analysis and with reference to relevant cultural, psychological, and philosophical scholarship, my exploration follows the threads of what Dark communicates about contemporary German masculinity in the face of trauma and how it reflects Western, White cultural thinking about the self.

Technical advantages embraced by blockchain, such as distributed ledger, P2P networks, consensus mechanisms and smart contracts, are highly compatible with addressing the security issues of transferring and storing judicial documents and obtaining the feedback and evaluation of judicial translation services in cases with foreign elements. Therefore, based on this, a consortium blockchain-based model for supervising the overall process of judicial translation services in cases with foreign elements is proposed.

Some judicial documents are required to be translated when there are language barriers in cases with foreign elements. The purpose of this paper is expected to address security issues, which is ignored, in the process of translating judicial documents.

The experimental results show that the model constructed in this paper can effectively guarantee the security and privacy of transferring and storing translated judicial documents in cases with foreign elements, and realize the credibility and traceability of feedbacks and evaluations of judicial translation services. In addition, the underlying network communications is stable and the speed for processing data can meet the requirements of practical application.

The research in this paper provides an innovative scheme for judicial translation services in cases with foreign elements. The model constructed is conducive to protecting the security of the transfer and storage of judicial documents and improving the efficiency and modernization ability of hearing cases with foreign elements.

The study aims to identify and understand the underlying behavioral tendencies and motivations influencing investor sentiments and examines the relationship between these underlying factors and investment decisions during the COVID-19-induced financial risks.

The study uses the primary data and information collected from 300 Indian retail equity investors using a nonprobability sampling technique, specifically purposive and snowball sampling. This research uses the insights from Phuoc Luong and Thi Thu Ha (2011) and Shefrin (2002) to delineate behavioral factors influencing investment decisions. Structural equation modeling estimates the causal relationship between underlying behavioral factors and investment decisions during the COVID-19-induced financial risks.

The study establishes that the “Regret Aversion,” “Gambler’s Fallacy” and “Greed” significantly influence investment decisions, and provide a comprehensive understanding of how psychological motivations shape investor behavior. Notably, “Mental Accounting” and “Conservatism” exhibit insignificance, possibly influenced by the unique socioeconomic context of the pandemic. The research contributes to 35% of variance understanding and prompts the researchers and policymakers to tailor investment strategies aligned to these behavioral tendencies.

The findings hold policy implications for investors and policymakers and provide tailored recommendations including investor education programs and regulatory measures to ensure a resilient and informed investment community in the context of India's evolving financial landscapes.

Theoretically, behavior tendencies and motivations have been strongly linked to investment decisions in the stock market. Yet, empirical evidence on this relationship is limited in developing countries where investors focus on risk management. To the best of the authors’ knowledge, this study is among the first to document the influence of underlying behavioral tendencies and motivation factors on investment decisions regarding retail equity in a developing country.

The purpose of this study is to present a methodical procedure on how to prepare event logs and analyse them through process mining, statistics and visualisations. The aim is to derive roots and patterns of quality deviations and non-conforming finished products as well as best practice facilitating employee training in the food processing industry. Thereby, a key focus is on recognising tacit knowledge hidden in event logs to improve quality processes.

This study applied process mining to detect root causes of quality deviations in operational process of food production. In addition, a data-ecosystem was developed which illustrates a continuous improvement feedback loop and serves as a role model for other applications in the food processing industry. The approach was applied to a real-case study in the processed cheese industry.

The findings revealed practical and conceptional contributions which can be used to continuously improve quality management (QM) in food processing. Thereby, the developed data-ecosystem supports production and QM in the decision-making processes. The findings of the analysis are a valuable basis to enhance operational processes, aiming to prevent quality deviations and non-conforming finished products.

Process mining is still rarely used in the food industry. Thereby, the proposed method helps to identify tacit knowledge in the food processing industry, which was shown by the framework for the preparation of event logs and the data ecosystem.

Fueled by the soaring popularity of the digital medium, consumers are increasingly relying on dynamic images to inform their decisions. However, little is known about how changes in the presentation of movement impacts these decisions. The purpose of this paper is to document whether and how movement speed–a fundamental characteristic of dynamic images in the digital medium–influences consumers' risk judgments and subsequent decisions.

Three experimental studies investigate the impact of movement speed displayed in the digital medium, focusing on different risk-laden domains including health (pilot study), gambling (Study 1) and stock market decisions (Study 2).

The authors find that faster movement speed displayed in the digital medium elevates consumers’ feelings of risk and elicits cautionary actions in response. The authors reveal a mechanism for this effect, showing that faster movement reduces feelings of control over outcomes, which predicts greater feelings of risk.

Future work could expand upon these findings by systematically examining whether certain individuals are more susceptible to movement speed effects in the digital medium. Research could also investigate whether different ways of experiencing movement speed (e.g. physical movement) similarly influence risk judgments and whether movement speed can have positive connotations outside of risky domains.

The authors offer important insights to marketing practitioners and public policymakers seeking to guide consumers’ judgments and decisions in risk-laden contexts through the digital medium.

By showing how movement speed alters judgments in risk-laden contexts, the authors contribute to literature on risk perception and the growing body of literature examining how moving images shape consumers’ behaviors.