Abstract
An all-passive, multipoint, and multiparameter optical monitoring system was developed and deployed in an industrial environment for the simultaneous measurement of methane concentration and other physical parameters. Methane is detected via rapid wavelength modulation spectroscopy (WMS) at 1648.2 nm and 4 MHz frequency. An attenuation invariant quantity defined by the peaks at 0, 4, and 8 MHz of the fast Fourier transform (FFT) of temporal signal is employed, characterized, and validated. Other parameters can concomitantly be measured by fiber Bragg grating (FBG) sensors operating in the 1520-1590 nm range. In the deployed system, the tested parameter was the temperature, which is an important quantity for gas monitoring. The system features a modular architecture that enables scalability up to 16 384 sensing points with an estimated less than 20-min acquisition cycle. In its current deployment, it monitors methane and temperature at eight locations using a single optical network. The system is intended to be used onshore and offshore platforms where the usual monitoring protocol consists of manual measurements usually performed three to four times a year and involves personal displacement and risky situations. Field tests at an onshore natural gas treatment unit (NGTU) demonstrated reliable performance and effective event detection, including undocumented nocturnal emissions, maneuvers at main shut-off valve, and partial plant shutdowns and restarts.

Abstract

Abstract
This paper presents a narrative review of power electronic converter topologies and architectures for energy conversion in green hydrogen production systems. A technical analysis is made regarding multiple performance metrics including total harmonic distortion (THD), current ripple, power factor, efficiency, and system complexity. The review examines AC/DC conversion topologies, covering both passive rectifiers and active front-end configurations with diverse transformer arrangements and harmonic mitigation techniques. DC/DC converter architectures are also analysed, distinguishing between non-isolated and isolated topologies, with emphasis on their operational principles, performance characteristics and practical suitability for hydrogen electrolyzer integration. Comparative analysis tables quantify key performance metrics between topologies across different power ranges and operational constraints. Additionally, the paper presents emerging technologies and modular converter structures, including current-source rectifiers, multiport converters, and modular multilevel architectures, alongside the transition toward solid-state transformers. Overall, this work provides a holistic review of the complete energy conversion chain from grid interface to electrolyzer, offering valuable insights for decision-support in topology selection in large-scale hydrogen production systems. In contrast with existing reviews, which often focus on individual conversion stages, this review seeks to fill a gap in the literature by summarizing the most relevant and technically mature topologies across the full chain with an evolutionary perspective.

Abstract
Understanding user behavior in search systems is essential for improving retrieval effectiveness and user satisfaction. While prior research has extensively examined general-purpose web search engines, domain-specific contexts-such as sports information-remain comparatively underexplored. In this study, we analyze over 400,000 interaction log entries from a sports-oriented search engine collected over a two-week period. Our analysis combines classic query-level metrics (e.g., frequency distributions, query lengths) with a detailed examination of click behavior, including entropy-based intent variability and a custom query quality scoring model. Compared to established baselines from general and specialized search environments, we observe a high proportion of new and single-term queries, as well as a notable lack of representativeness among top queries. These findings reveal patterns shaped by the event-driven and entity-centric nature of sports content, offering actionable insights for the design of domain-specific retrieval systems.

Abstract
The aim of this work is to explore normalising flows to detect anomalous behaviours which is an essential task mainly for surveillance systems-related applications. To accomplish that, a series of ablation studies were performed by varying the parameters of the Spatio-Temporal Graph Normalising Flows (STG-NF) model [3] and combining it with attention mechanisms. Out of all these experiments, it was only possible to improve the state-of-the-art result for the UBnormal dataset by 3.4 percentual points (pp), for the Avenue by 4.7 pp and for the Avenue-HR by 3.2 pp. However, further research remains urgent to find a model that can give the best performance across different scenarios. The inaccuracies of the pose tracking and estimation algorithm seems to be the main factor limiting the models' performance. The code is available at https://github.com/AnaFilipaNogueira/Abnormal-Human-Behaviour-Detection- using-Normalising-Flows-and- Attention-Mechanisms.

Abstract
Maritime transport faces increasing decarbonisation requirements, placing new demands on port energy systems. Yet most existing studies analyse isolated components or short time horizons, limiting their usefulness for long-term planning. This work develops a holistic, least-cost optimisation model of the Port of Sines energy system using OSeMOSYS, integrating electricity and fuel consumption across port operations and fuel-management processes from 2020 to 2050.The study evaluates alternative technology pathways and policy measures, including carbon taxation, national emission-reduction targets, and the adoption of an innovative ocean-going vessel fleet. Results show that electrification, driven by onshore power supply and renewable expansion, is the most cost-effective decarbonisation route, while its performance depends on local generation capacity and the carbon intensity of the electricity mix. Policy mechanisms and fleet innovation further influence the timing and depth of emissions reductions. Overall, the model provides a replicable framework to support strategic port decarbonisation planning.