Abstract
Low-finesse Fabry-Perot interferometers (FPI) with a plano-convex geometry are fabricated in ULE (R) glass through ultrafast laser machining. With this geometry, it is possible to overcome beam divergence effects that contribute to the poor fringe visibility usually observed in 100-mu m or longer planar-planar FPIs. By replacing the planar surface with a spherical one, the diverging beam propagating through the cavity is re-focused back at the entrance of the lead-in fiber upon reflection at this curved interface, thereby balancing out the intensities of both interfering beams and enhancing the visibility. The design of a 3D shaped cavity with a spherical sidewall is only made possible through fs-laser direct writing followed by chemical etching. In this technique, the 3D volume is reduced to writing of uniformly vertically spaced 2D layers with unique geometry, which are then selectively removed during chemical etching with HF acid. The radius of curvature that maximizes fringe visibility is computed using a numerical tool that is experimentally validated. By choosing the optimal radius of curvature, uniform visibilities in the range of 0.98-1.00 are measured for interferometers produced with cavity lengths spanning from 100 to 1000 mu m.

Abstract
Knowledge of Social Engineering is crucial to prevent potential attacks related to organizational Information Security. The objective of this paper aims to identify the most common social engineering techniques, success attack factors, and obstacles, as well as the good practices and frameworks that could be adopted concerning their mitigation. As an analysis methodology, a Systematic Literature Review was carried out. The findings revealed that the discussion about SE attacks has increased and that the most imminent threat is phishing. Exploiting human vulnerabilities is a growing threat when the attack is not carried out directly through technical means. There continue to be more technical attacks than non-technical attacks. Encouraging organizational security prevention, like training, education, technical controls, process development, defense in detail, and the development of security policies, should be considered mitigating factors for the negative impact of SE attacks. Most SE frameworks/models are focused on attack techniques and methods, mostly on technical components, decorating human factor. As a novelty, we found the opportunity to develop a new framework that could improve coverage of the gaps found, supported on security international standards, that could help and support researchers in developing their work, understanding open research topics, and providing a clearer understanding of this type of threat. © 2024 by the authors. Licensee ESJ, Italy.

Abstract
The implementation of traffic differentiation measures by internet service providers (ISPs) has raised concerns regarding net neutrality, potentially leading to discriminatory practices that challenge existing regulatory frameworks. The complexity of this issue intensifies with the advent of 5G networks as they dynamically assemble elements of the physical infrastructure to create logically segregated domains customised to accommodate usage scenarios with specific requirements, resulting in the categorisation of users, applications, and services into distinct groups which possess the capacity to disrupt the non-discriminatory treatment of data flows. Within this context, a pivotal question arises: how can regulatory authorities effectively evaluate traffic differentiation in 5G networks? In response, this paper proposes an innovative application of the standardised network data analytics function (NWDAF) to facilitate the assessment of internet traffic differentiation. We introduce this novel concept and demonstrate its implementation through a proof -of -concept prototype. By leveraging the NWDAF, regulators may obtain direct and automatic access to performance metrics of 5G networks, enabling the analysis of the traffic management mechanisms employed by ISPs.

Abstract
In the energy production sector, increasing the quantity and efficiency of renewable energies, such as hydropower plants, is crucial to mitigate climate change. This paper proposes a new and flexible model for optimising operational decisions in watershed systems with interconnected dams. We propose a systematic representation of watersheds by a network of different connection points, which is the basis for an efficient Mixed-Integer Linear Programming model. The model is designed to be adaptable to different connections between dams in both main and tributary rivers. It supports decisions on power generation, pumping and water discharge, maximising profit, and considering realistic constraints on water use and factors such as future energy prices and weather conditions. A relax-and-fix heuristic is proposed to solve the model, along with two heuristic variants to accommodate different watershed structures and sizes. Methodological tests with simulated instances validate their performance, with both variants achieving results within 1% of the optimal solution faster than the model for the tested instances. To evaluate the performance of the approaches in a real-world scenario, we analyse the case study of the C & aacute;vado watershed (Portugal), providing relevant insights for managing dam operations. The model generally follows the actual decisions made in typical situations and flood scenarios. However, in the case of droughts, it tends to be more conservative, saving water unless necessary or profitable. The model can be used in a decision-support system to provide decision-makers with an integrated view of the entire watershed and optimised solutions to the operational problem at hand.

Abstract
This paper describes the relevant research activities that are being carried out on the development of a novel shotcrete technology capable of applying, autonomously and in real time, fibre reinforced shotcrete (FRS) with tailored properties regarding the optimum structural strengthening of railway tunnels (RT). This technique allows to apply fibre reinforced concrete (FRC) of strain softening (SSFRC) and strain hardening (SHFRC) according to a multi -level advanced numerical simulation that considers the relevant nonlinear features of these FRC, as well as their interaction with the surrounding soil, for an intended strengthening performance of the RT. Building information modelling (BIM) is used for assisting on the development of data files of the involved design software, integrating geometric assessment of a RT, damages from inspection and diagnosis, and the characteristics of the FRS strengthening solution. A dedicated computational tool was developed to design FRC with target properties. The preliminary experimental results on the evaluation of the relevant mechanical properties of the FRS are presented and discussed, as well as the experimental tests on the bond between FRS and current substrates found in RT. Representative numerical simulations were performed to demonstrate the structural performance of the proposed FRS -based strengthening technique. Computational tools capable of assuring, in real time, the aimed thickness of the layers forming the FRS strengthening shell were also developed. The first generation of a mechanical device for controlling the amount of fibres to be added, in real time, to the FRS mixture was conceived, built and tested. A mechanism is also being developed to improve the fibre distribution during its introduction through the mechanical device to avoid fibre balling. This work describes the relevant achievements already attained, as introduces the planned future initiatives in the scope of this project.

Abstract
Canine hip dysplasia (CHD) screening relies on accurate positioning in the ventrodorsal hip extended (VDHE) view, as even mild pelvic rotation can affect CHD scoring and impact breeding decisions. This study aimed to assess the association between pelvic rotation and asymmetry in obturator foramina areas (AOFAs) and to develop a computer vision model for automated AOFA measurement. In the first part, 203 radiographs were analyzed to examine the relationship between pelvic rotation, assessed through asymmetry in iliac wing and obturator foramina widths (AOFWs), and AOFAs. A significant association was found between pelvic rotation and AOFA, with AOFW showing a stronger correlation (R-2 = 0.92, p < 0.01). AOFW rotation values were categorized into minimal (n = 71), moderate (n = 41), marked (n = 37), and extreme (n = 54) groups, corresponding to mean AOFA +/- standard deviation values of 33.28 +/- 27.25, 54.73 +/- 27.98, 85.85 +/- 41.31, and 160.68 +/- 64.20 mm(2), respectively. ANOVA and post hoc testing confirmed significant differences in AOFA across these groups (p < 0.01). In part two, the dataset was expanded to 312 images to develop the automated AOFA model, with 80% allocated for training, 10% for validation, and 10% for testing. On the 32 test images, the model achieved high segmentation accuracy (Dice score = 0.96; Intersection over Union = 0.93), closely aligning with examiner measurements. Paired t-tests indicated no significant differences between the examiner and model's outputs (p > 0.05), though the Bland-Altman analysis identified occasional discrepancies. The model demonstrated excellent reliability (ICC = 0.99) with a standard error of 17.18 mm(2). A threshold of 50.46 mm(2) enabled effective differentiation between acceptable and excessive pelvic rotation. With additional training data, further improvements in precision are expected, enhancing the model's clinical utility.