Abstract
Technological advances in global communications depend significantly on robust and efficient long-distance infrastructures. One notable example is the submarine cable network. Installed on the ocean floor, these cables use fiber optic technology to transmit large volumes of data at high speed and low latency between continents. Beyond their primary communication function, recent innovations allow these cables to serve as Distributed Acoustic Sensing (DAS) systems, effectively converting tens of kilometers of passive fiber into massive, coherent arrays of vibration sensors. The primary objective of this project is to enhance maritime surveillance capabilities by integrating DAS technology with advanced kinematic modeling. This paper establishes a rigorous physical and mathematical framework for interpreting the acoustic signatures of surface vessels detected by bottom-mounted fibers. We derive the complete opto-acoustic transfer function, formulate the hyperbolic moveout equations based on a moving point-source solution to the wave equation, and implement a stochastic inversion scheme using Differential Evolution. By optimizing a correlation-based loss function, we demonstrate the ability to recover vessel trajectory, speed, and depth from complex interferometric patterns with speed estimation errors consistently below 1%. This approach allows for the extraction of quantitative physical parameters from raw optical data, bridging the gap between photonics and hydroacoustics.

Abstract
Blending green hydrogen into gas networks is subject to strict quality regulation. As Europe diversifies its Liquefied Natural Gas supply, existing literature often ignores the extreme chemical variability of these sources by assuming a static composition. This study proposes a nonlinear steady-state optimization model, strictly adhering to European standards, to maximize hydrogen injection across eight real-world LNG profiles. Results reveal severe sensitivity to the carrier gas: lean gas (Trinidad and Tobago, USA) restricts maximum hydrogen integration to 8.89% and 11.40% by volume due to insufficient heavy hydrocarbons. Conversely, carbon-rich gas (Nigeria) allows up to 20.10%, although inert gases degrade this capacity. Ultimately, this 20.10% maximum blend yields only a 6.77% emission reduction. The imported chemical profile dictates absolute limits, proving that static universal hydrogen quotas are thermodynamically unachievable year-round without continuous dynamic quality tracking. © 2026

Abstract

Abstract
Small-and-medium-sized enterprises (SMEs) increasingly depend on business partnerships to access markets and scale operations, yet they often face trust barriers during contract formation due to the complexity of the verification of their cybersecurity posture and compliance status by their partners. This problem is intensified by rising regulatory expectations, notably the EU Cyber Resilience Act (CRA), which many SMEs struggle to interpret and operationalize under constraints of budget, skills, and fragmented responsibilities. This study adopts a Design Science Research approach to blueprint and evaluate a lightweight mapping framework that links commonly implemented security controls to CRA requirements and to widely recognized benchmarks (ISO/IEC 27001 and CIS). Grounded in Institutional Theory and Socio-Technical Systems Theory, the artefact translates regulatory obligations into actionable, evidence-backed controls and produces partner-facing outputs that support transparency in negotiations and service level agreements. The framework is iteratively co-created with a multidisciplinary expert community. Expected contributions include a practical mechanism for making cybersecurity maturity visible, accelerating partnership formation, and enabling sustainable interorganizational relationships while remaining feasible for resource-constrained SMEs.

Abstract

Abstract
The need to improve the flexibility and dynamism of the Electric Power Systems (EPS) has driven the development and integration of new devices. Among these, FACTS controllers are particularly notable for their ability to regulate multiple system variables. Incorporating FACTS into the grid requires integrating their electrical models into the analysis and operational tools of the EPS, ensuring precise monitoring and effective system control. This article presents novel steady-state models for FACTS controllers, specifically designed for decoupled state estimation methods. The framework updates the algorithm decoupled and model decoupled state estimators and introduces the modified algorithm decoupled estimator, which offers enhanced robustness and convergence. These improvements are validated through theoretical analysis and simulations. The methodology introduces new state variables and decoupled nonlinear functions to represent FACTS controllers, enabling seamless integration into decoupled estimation frameworks. The study assesses the effectiveness of bad data processing using the Largest Normalized Residual Test (LNR-Test), ensuring robustness under decoupled FACTS modeling. Simulations on the IEEE 30-bus and IEEE 118-bus test systems include shunt, series, series-shunt, and multiple FACTS controllers, as well as single and multiple bad data. Results demonstrate the accuracy and effectiveness of the decoupled estimators with FACTS controllers and confirm the practical applicability of LNR-Test within the proposed approaches.