The temporality of building: European and Chinese perspectives on architecture and heritage

This book examines the role that time plays in the life of buildings, adopting a comparative study of this influence between European and Chinese traditions. Whilst issues of time in architecture have attracted increasing interest by academics in the West, challenging the dominant modernist precepts of space, there is little understanding of the subject in China and how these compare to historical and contemporary perspectives in Europe. A guiding premise of the investigation is that notions of building time require insight into how cultural habits commingle with natural rhythms, or what David Leatherbarrow calls “concurrency”. Rather than examining specific buildings, the first three chapters apply three key themes (language, ritual and heritage) as cultural lenses to reveal differences and similarities between the two traditions. Through these lenses, buildings, interiors and their exterior spaces (churches/cathedrals, temples, palaces, gardens and courtyard houses) are explored to demonstrate how building time involves particular situations/settings and their correlating relationships to past traditions. In the final chapter we consider notions of time in the context of contemporary buildings in Europe and China, drawing on the earlier historical investigations and addressing globalising influences. This book would be of interest to architects, architectural theorists, historians, philosophers, sociologists and anthropologists

Vile sovereignty: the carnival of power

In this paper we seek to extend Bakhtin’s reading of the folk carnival and apply it to help understand the carnivalesque, performative aspects of state power. Drawing on the work of Agamben, Foucault, Lacan and Žižek and recent scholarship on the role of laughter in the Stalinist totalitarian culture, we argue that the state can also laugh and that it can have its own carnival tradition as well. To explore what we propose to call the carnival of power, we examine three iterations of this tradition: the festive exercise of state violence, state carnivalisers, and the carnivalesque style in governance

Framework for analysis of the logical vulnerability of authentication procedures

While AI has made strides in knowledge and action modelling, challenges remain in addressing security concerns like logical vulnerabilities in authentication policies. These vulnerabilities arise from flawed or missing authentication mechanisms, making operations unintentionally accessible. Our objective is to model the domain and find such vulnerabilities. Our approach is based on a novel three-level framework, specifically focusing on identifying logical vulnerabilities in authentication policies. Each level is built on top of the previous one. The first is the ontological level, where we model the static domain using Description Logics serialised as Ontology Web Language, providing a foundational representation of classes and relationships. The second is the logical level, where action rules, capturing system dynamics, are formalised using Horn Clause and First-Order Logic, serialised as Semantic Web Rule Language. We address the frame problem through efficient parameter utilisation as a side effect. The third is the analytical level, where we transform action rules into a policies graph to validate and visualise them and transform assertions into an instance graph to visualise the specific instance of the world to facilitate the analysis. We leverage the reasoner and control constant in an algorithmic approach, which detects vulnerabilities in the policies by finding vulnerable situations. We demonstrate the framework’s effectiveness and practicality through experimental evaluation with two real-world applications. Results highlight its scalability, explainability, and accuracy in detecting vulnerabilities, showcasing its potential to enhance security policy analysis

Antiviral activity of rhamnolipids nano-micelles against rhinoviruses—in silico docking, molecular dynamic analysis and in-vitro studies

Hospital-acquired infections (HAIs) previously focused mainly on multidrug-resistant (MDR) bacteria, with less attention on viruses. The COVID-19 pandemic highlighted the importance of controlling viral infections. Human rhinoviruses (HRVs) are among the viruses responsible for HAIs. HRVs are non-enveloped viruses that infect the upper airways after airborne or direct transmission. Due to their lack of a membrane envelope, HRVs exhibit moderate resistance to commonly applied alcoholic disinfectants. Therefore, there is a significant need to develop alternative disinfection and hand sanitation strategies to control HRV infections in healthcare settings without posing a risk to human health. The antimicrobial activity and safety of rhamnolipids and rhamnolipids nano-micelles (RMN) against MDR-bacteria and several viruses, including SARS-CoV-2, were confirmed recently. Also, we previously demonstrated the superior antimicrobial activity of RMN over rhamnolipids. In the current study, molecular docking demonstrated the weak interactions of rhamnolipids with HRV-1A (minor group) compared to HRV-14 (major group), suggesting a superior antiviral activity of rhamnolipids towards major group rhinoviruses. To biologically validate these data, RMN was prepared and characterized, and then antiviral activity against HRV-16 (major group) and HRV-1B (minor group) infection of HeLa cells was assessed. RMN showed a complete inhibition of HRV-16 infection with recovery of 100% of HeLa cell viability. In contrast, only partial inhibition of HRV-1B infection with approximately 50% protection against infection was observed. Therefore, RMN might be recommended as a disinfectant and/or a hand sanitizer component to control the spread of RVs in hospital care settings or elsewhere to reduce the incidence of respiratory infections

Conflict of Interest: justifying international cooperation in populist discourse

Contrary to the stereotypical assumption that the foreign policy of populists is geared towards conflict, much of the literature in recent years has converged on the understanding that populism results in a complex and often seemingly incoherent mix of cooperation and confrontation. Populist leaders often adopt a confrontational stance towards other states and international institutions, yet they are also capable of striking deals, defusing tensions and reconciling with multilateral settings. This inconsistency is due to a variety of factors like geopolitical and economic pressures or the thick-ideological proclivities of populists. But in this article, we are interested in how populists reconcile the contradictory trend to antagonize internationally but end up striking deals. Drawing on the literature on populist discourses and a view of foreign policy as political management of state-society relations, we argue that this reconciliation takes place primarily at a discursive level, as populists deploy a discourse of cooperation that remains consistent with the binary and Manichean logic of populism. We identify three populist discursive strategies of justifying cooperation after conflict: elite-splitting; issue-bundling and audience-hopping. We demonstrate our argument by comparing two cases of populist compromising with the EU following a protracted period of confrontation: Greece’s acceptance of a third bailout from the Eurozone under Alexis Tsipras in 2015; and Britain’s signing of a final Brexit deal under Boris Johnson in 2020

On refactorization problems and rational Lax matrices of quadrirational Yang-Baxter maps

We present rational Lax representations for one-component parametric quadrirational Yang–Baxter maps in both the abelian and non-abelian settings. We show that from the Lax matrices of a general class of non-abelian involutive Yang–Baxter maps (K-list), by considering the symmetries of the K-list maps, we obtain compatible refactorization problems with rational Lax matrices for other classes of non-abelian involutive Yang–Baxter maps (Λ, H and F lists). In the abelian setting, this procedure generates rational Lax representations for the abelian Yang–Baxter maps of the F and H lists. Additionally, we provide examples of non-involutive multi-parametric Yang–Baxter maps, along with their Lax representations, which lie outside the preceding lists

Chemical analyses and therapeutic properties of plant extracts

It has been almost 20 years since the World Health Organization (WHO) established the International Regulatory Co-operation for Herbal Medicines (IRCH), as part of a WHO Traditional Medicine Strategy. Ensuring the efficacy, quality, and safety of herbal medicines is a key component of the strategy. The articles presented in this Special Issue address this component and represent a growing body of work in which a plethora of bioactive properties, of the therapeutic potential, of plants extracts have been identified. The obvious and consistent questions that arise from such studies are what are the contributions of the plants’ constituents to these properties and how significant is the therapeutic potential identified? The factors, which some might call challenges, that need to be considered in answering such a question effectively include the impact of different extraction techniques on the bioactive properties of plant extracts and developing and utilizing methods that simulate and model as closely as possible disease processes in humans. The aim of this Special Issue was to invite submissions that explored and addressed these factors as part of the process of gaining greater insights into how the bioactive properties of plant extracts (1) are conferred by their constituents and (2) can be exploited in developing new therapies for certain conditions

AI surveillance in education: unpacking ethical dilemmas and the snake-oil promises of AI-infused technosolutionism

This chapter examines the ethical implications of the increasing integration of AI surveillance technologies within educational settings, including proctoring software, classroom monitoring tools, and behavioral analytics. The swarm approach employed reflects diverse perspectives on this complex issue. It unpacks how AI surveillance reduces multifaceted students and faculty to data points, disproportionately targeting marginalized learners and misreading neurodivergent behaviors. The chapter critiques the snake's oil sales pitch of AI-infused technosolutionist discourse and foregrounds concerns regarding the erosion of student and lecturer autonomy, the alteration of student-lecturer relationships and the erosion of trust, the normalization of surveillance, and the amplification of existing inequalities and biases through algorithmic processes. The chapter concludes by emphasizing the need for educators to foster a learning environment that amplifies human potential

AI-powered system for an efficient and effective cyber incidents detection and response in cloud environments

The growing complexity and frequency of cyber threats in cloud environments call for innovative and automated solutions to maintain effective and efficient incident response. This study tackles this urgent issue by introducing a cutting-edge AI-driven cyber incident response system specifically designed for cloud platforms. Unlike conventional methods, our system employs advanced Artificial Intelligence (AI) and Machine Learning (ML) techniques to provide accurate, scalable, and seamless integration with platforms like Google Cloud and Microsoft Azure. Key features include an automated pipeline that integrates Network Traffic Classification, Web Intrusion Detection, and Post-Incident Malware Analysis into a cohesive framework implemented via a Flask application. To validate the effectiveness of the system, we tested it using three prominent datasets: NSL-KDD, UNSW-NB15, and CIC-IDS-2017. The Random Forest model achieved accuracies of 90%, 75%, and 99%, respectively, for the classification of network traffic, while it attained 96% precision for malware analysis. Furthermore, a neural network-based malware analysis model set a new benchmark with an impressive accuracy rate of 99%. By incorporating deep learning models with cloud-based GPUs and TPUs, we demonstrate how to meet high computational demands without compromising efficiency. Furthermore, containerisation ensures that the system is both scalable and portable across a wide range of cloud environments. By reducing incident response times, lowering operational risks, and offering cost-effective deployment, our system equips organizations with a robust tool to proactively safeguard their cloud infrastructure. This innovative integration of AI and containerised architecture not only sets a new benchmark in threat detection but also significantly advances the state-of-the-art in cybersecurity, promising transformative benefits for critical industries. This research makes a significant contribution to the field of AI-powered cybersecurity by showcasing the powerful combination of AI models and cloud infrastructure to fill critical gaps in cyber incident response. Our findings emphasise the superior performance of Random Forest and deep learning models in accurately identifying and classifying cyber threats, setting a new standard for real-world deployment in cloud environments

Impact of COVID-19 on the prevalence of multi-drug-resistant bacteria: a literature review and meta-analysis

The COVID-19 pandemic affected the global healthcare delivery system, raising concerns about its influence on antimicrobial resistance (AMR). This systematic review and meta-analysis assessed the impact of the COVID-19 pandemic on the prevalence of MDR bacteria in different healthcare environments. A systematic search was carried out in PubMed-MEDLINE, Embase, Web of Science, BIOSIS, Scopus, and Google Scholar for articles published from December 2019 to January 2024. After screening 77 full-text studies, 28 studies were included in the analysis. The inclusion criteria included original human studies presenting MDR bacteria incidence before and during/after COVID-19 with reference to Carbapenem-resistant Acinetobacter baumannii, Carbapenem-resistant Enterobacteriaceae, Vancomycin Resistant Enterococci, Carbapenem-Resistant Pseudomonas aeruginosa, Methicillin-resistant Staphylococcus aureus, and Extended-Spectrum Beta-Lactamase-producing Enterobacteriaceae. The overall odds ratio (OR = 0.91, 95% CI: 0.70-1.17) indicates no significant change in the prevalence of multidrug-resistant (MDR) bacterial infection between the pre-COVID-19 and the COVID-19 period. There was no significant change in the prevalence of MRSA, ESBL, and VRE pre- and post-COVID. However, there was a significant reduction in the prevalence of CR-Ab, CRE, and CRPA pre- and during/after-COVID-19. MDR prevalence was significantly increased in Asia (18%) while it decreased slightly in North America (10.3%), showing variations in antibiotic use. The findings show that COVID-19 has different effects on the prevalence of MDR bacteria across geographical regions and healthcare facilities. [Abstract copyright: © 2025. The Author(s), under exclusive licence to Springer Nature Switzerland AG.