Abstract
In an era characterized by extensive use of and reliance on information and communications technology (ICT), cyber-physical power systems (CPPSs) have emerged as a critical integral of modern power infrastructures, providing vital energy sources to consumers, communities, and industries worldwide. The integration of ICT in these systems, while beneficial, introduces a rapidly evolving range of cybersecurity challenges that significantly threaten their confidentiality, integrity, and availability. To address this, our article offers a comprehensive and timely survey of the current landscape of cyber vulnerabilities in CPPS, reflecting the latest developments in the field up to the present. This includes an in-depth analysis of the diverse types of cyber threats to CPPS and their potential consequences, underscoring the necessity for a broad, multidisciplinary approach. Our review is distinguished by its thoroughness and timeliness, covering recent research to offer one of the most current overviews of cybersecurity in CPPSs. We adopt a holistic perspective, integrating technical, societal, environmental, and policy implications, thereby providing a more comprehensive understanding of cybersecurity in CPPSs. We delve into the complexities of cyberattacks, exploring sophisticated, targeted attacks alongside common threats, and emphasize the dynamic nature of cyber threats, providing insights into their evolution and future trends. Additionally, our review highlights critical yet often overlooked challenges, such as system visibility and standardization in security protocols, arguing their significance in enhancing CPPS resilience. Furthermore, our work gives special attention to the aspects of restoration and recovery postcyberattack, an area less emphasized in the existing literature. Through this comprehensive overview of the current state and evolving challenges of CPPS security, our article serves as an indispensable resource for research, practice, and policymaking dedicated to safeguarding the safety, reliability, and resilience of ICT-empowered energy systems.

Abstract
The early and accurate detection and the grading characterization of brain cancer will generate a positive impact on the treatment plan of those patients. AI-based models can help analyze the Magnetic Resonance Imaging (MRI) to make an initial assessment of the tumor grading. The objective of this work was to develop an Al-based model to classify the grading of the tumor using the MRI. Two regions of interest were explored, with several levels of complexity for the neural network architecture, and Iwo strategies to deal with Unbalanced data. The best results were obtained for the most complex architecture (Resnet50) with a combination of weighted random sampler and data augmentation achieving a balanced accuracy of 62.26%. This work confirmed that complex problems required a more dense neural network and strategies to deal with the unbalanced data.

Abstract
With the proliferation of ODR service providers, there is a critical necessity to establish mechanisms supporting their functioning, particularly while designing ODR processes. This article aims to examine the impact of process modelling using BPMN, and of its relevance in the integration of AI into ODR processes within the EU. BPMN allows a meticulous depiction of all the ODR process steps, stakeholders, and underlying data in structured formats that are readable and interpretable by both humans and AI, which enables its integration. The advantages include predictive analysis, identification of opportunities for continuous improvement, operational efficiency, cost and time reduction, and enhanced accessibility for self-represented litigants. Additionally, the transparency afforded by explicitly incorporating AI in BPMN notation fosters a clearer comprehension of processes, facilitating management and informed decision-making. Nevertheless, it remains imperative to address ethical concerns such as algorithmic bias, fairness, and privacy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Abstract

Abstract
The Single Supervisory Mechanism (SSM) was implemented as a first step towards a Banking Union in November 2014. This paper investigates the impact of the SSM on Eurozone banks' efficiency and position of best-practice frontier. It is based on a balanced panel analysis of 931 European bank-year observations from 2011 to 2017 (133 banks, seven years). The study uses Data Envelopment Analysis and a difference-in-differences approach to explore the evolution of banking performance. We found that the SSM had a negative impact on the efficiency levels of Eurozone banks, particularly in the year after the introduction of the mechanism. Additionally, we observed that the frontier formed by non-Eurozone European Union banks is more productive than the frontier of Eurozone banks in all the years analysed. Both efficiency and frontier position show evidence of a recovery trend in more recent years for both groups. We also found that while Equity-to-Asset Ratio, Return on Average Assets and Gross Domestic Product per capita positively impacted banks' efficiency, domestic credit provided by banks expressed as %GDP had a negative impact on efficiency.

Abstract
The Internet -of -Things (IoT) has created a complex environment where hardware and software interact in complex ways. Despite being a prime candidate for applying well -established software engineering practices, IoT has not seen the same level of adoption as other areas, such as cloud development. This discrepancy is even more evident in the case of edge devices, where programming and managing applications can be challenging due to their heterogeneous nature and dependence on specific toolchains and languages. However, the emergence of WebAssembly as a viable solution for running high-level languages on some devices presents an opportunity to streamline development practices, such as DevOps. In this paper, we present WASMICO - a firmware and command -line utility that allows for the execution and management of application lifecycles in microcontrollers. Our solution has been benchmarked against other state-of-the-art tools, demonstrating its feasibility, novel features, and empirical evidence that it outperforms some of the most widely used solutions for running high-level code on these devices. Overall, our work aims to promote the use of wellestablished software engineering practices in the IoT domain, helping to bridge the gap between cloud and edge development.