Abstract
Industry 4.0 has brought modernization to the production system through the network integration of the constituent entities which, combined with the evolution of information technology, has enabled an increase in productivity, product quality, optimization of production costs, and product customization to customer needs. Despite the complexity of human thought, artificial intelligence tries to replicate it in algorithms, creating models capable of processing databases with a high volume of information, and generating valuable information for decision making. Within this area, there are subfields, such as Machine Learning and Deep Learning, which, through mathematical models, define patterns to predict output data from known input data. In addition to this type of algorithm, there are metaheuristic models capable of optimizing the parameters required in Machine Learning and Deep Learning algorithms. These intelligent systems have applications in various areas such as industry, construction, health, logistics processes, and maintenance management, among others. This paper focuses on Artificial Intelligence models addressing Industry 4.0 approach. © 2024 The Author(s). Published by Elsevier B.V.

Abstract
METIS, the Mid-infrared ELT Imager and Spectrograph, will be one of the first instruments to be used at ESO's 39m Extremely Large Telescope (ELT), that is currently under construction. With that, a number of firsts are to be addressed in the development of METIS' single-conjugate Adaptive Optics (SCAO) system: the size of the telescope and the associated complexity of the wavefront control tasks, the unique scientific capabilities of METIS, including high contrast imaging, the interaction with the newly established, integrated wavefront control infrastructure of the ELT, the integration of the near-infrared Pyramid Wavefront Sensor and other key Adaptive Optics (AO) hardware embedded within a large, fully cryogenic instrument. METIS and it's AO system have passed the final design review and are now in the manufacturing, assembly, integration and testing phase. The firsts are approached through a compact hard- and software design and an extensive test program to mature METIS SCAO before it is deployed at the telescope. This program includes significant investments in test setups that allow to mimic conditions at the ELT. A dedicated cryo-test facility allows for subsystem testing independent of the METIS infrastructure. A telescope simulator is being set up for end-to-end laboratory tests of the AO control system together with the final SCAO hardware. Specific control algorithm prototypes will be tested on sky. In this contribution, we present the progress of METIS SCAO with an emphasis on the preparation for the test activities foreseen to enable a successful future deployment of METIS SCAO at the ELT.

Abstract
Anonymity networks like Tor significantly enhance online privacy but are vulnerable to correlation attacks by state-level adversaries. While covert channels encapsulated in media protocols, particularly WebRTC-based encapsulation, have demonstrated effectiveness against passive traffic correlation attacks, their resilience against active correlation attacks remains unexplored, and their compatibility with Tor has been limited. This paper introduces TorKameleon, a censorship evasion solution designed to protect Tor users from both passive and active correlation attacks. TorKameleon employs K-anonymization techniques to fragment and reroute traffic through multiple TorKameleon proxies, while also utilizing covert WebRTC-based channels or TLS tunnels to encapsulate user traffic.

Abstract
In a housing market of Shapley and Scarf, each agent is endowed with one indivisible object and has preferences over all objects. An allocation of the objects is in the (strong) core if there exists no (weakly) blocking coalition. We show that, for strict preferences, the unique strong core allocation respects improvement-if an agent's object becomes more desirable for some other agents, then the agent's allotment in the unique strong core allocation weakly improves. We extend this result to weak preferences for both the strong core (conditional on nonemptiness) and the set of competitive allocations (using probabilistic allocations and stochastic dominance). There are no counterparts of the latter two results in the two-sided matching literature. We provide examples to show how our results break down when there is a bound on the length of exchange cycles. Respecting improvements is an important property for applications of the housing markets model, such as kidney exchange: it incentivizes each patient to bring the best possible set of donors to the market. We conduct computer simulations using markets that resemble the pools of kidney exchange programs. We compare the game-theoretical solutions with current techniques (maximum size and maximum weight allocations) in terms of violations of the respecting improvement property. We find that game-theoretical solutions fare much better at respecting improvements even when exchange cycles are bounded, and they do so at a low efficiency cost. As a stepping stone for our simulations, we provide novel integer programming formulations for computing core, competitive, and strong core allocations.

Abstract
Over the years, mobile networks were deployed using monolithic hardware based on proprietary solutions. Recently, the concept of open Radio Access Networks (RANs), including the standards and specifications from O-RAN Alliance, has emerged. It aims at enabling open, interoperable networks based on independent virtualized components connected through open interfaces. This paves the way to collect metrics and to control the RAN components by means of software applications such as the O-RAN-specified xApps. We propose a private standalone network leveraged by a mobile RAN employing the O-RAN architecture. The mobile RAN consists of a radio node (gNB) carried by a Mobile Robotic Platform autonomously positioned to provide on-demand wireless connectivity. The proposed solution employs a novel Mobility Management xApp to collect and process metrics from the RAN, while using an original algorithm to define the placement of the mobile RAN. This allows for the improvement of the connectivity offered to the User Equipments.

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.