Abstract
In this paper is presented a mixed-integer linear programming (MILP) model that maximizes the Photovoltaic-based (PV-based) hosting capacity (HC) in unbalanced and active distribution networks. The model takes into account the controlled charge of electric vehicles (EVs) and incorporates a demand-response program (DRP), for demand-side load shifting. The model's solution determines the optimal operation of distributed generators (DGs), switched capacitor banks (SCBs), energy storage devices (ESDs), coordination of the EVs charging, and DRP. Linear formulation is obtained from a mixed-integer non-linear programming (MINLP) model, ensuring tractability and guarantee convergence, since it can be efficiently solved using commercial optimization solvers of convex optimization. The model's effectiveness is demonstrated through tests on a 123-bus, three-phase unbalanced distribution system. Four case studies are conducted to assess the effect of different distributed energy resources (DERs). Results show that the simultaneous optimization of DERs, EVs charging and DR scheduling can significantly increase the PV-based HC -reaching up more than the substation capacity- while reducing total power losses. These findings demonstrate the technical potential of integrated DER coordination in enhancing PV penetration and improving the operational efficiency of active distribution systems.

Abstract
Reinforced concrete structures form the backbone of civil infrastructure due to their durability, longevity, affordability, and availability. However, aging concrete poses challenges, with decay often beginning internally and becoming visible only at advanced stages, leading to costly repairs, restricted functionality, and safety risks. To address these challenges, sensors are crucial for enhancing infrastructure resilience and optimizing repairs. This study employs multimode optical fibers to monitor concrete curing, water ingress, relative humidity (RH), cement paste carbonation, and rebar corrosion. Four sensors monitor changes in reflection at the fiber tip of a 600 mu m multimode fiber (MMF) using LEDs and photodiodes, connected via a fiber bundle containing two 200 mu m MMF. Variations in the refractive index around the fiber tip are used to monitor water throughout the concrete lifecycle, including curing, RH changes and water intrusion. Colorimetric changes in a cement paste layer and an iron-thin film are used to monitor carbonation and corrosion. The curing sensor is temperature-independent and correlates strongly with cumulative heat release from cement hydration (R=0.95). The RH sensor monitors up to and beyond 100% RH, detecting water intrusion. The corrosion sensor detects early corrosion stages and distinguishes between reflection losses from corrosion and mechanical changes. The layer of cement paste for carbonation monitoring increases reflected intensity by 17% due to carbonation, with 63% of the increase occurring in 80 minutes in a 3% CO2 atmosphere. The broad monitoring scope and low implementation cost make this sensor a unique option among commercially available solutions for structural health monitoring of reinforced concrete.

Abstract
The growing demands of the Blue Economy are increasingly supported by sensing platforms, including as Autonomous Surface Vehicles (ASVs) and Autonomous Underwater Vehicles (AUVs). Multimodal Underwater Wireless Networks (MUWNs), which may combine acoustic, radio-frequency, and optical wireless technologies, enhance underwater data transmission capabilities. Although Delay-Tolerant Networks (DTNs) address connectivity intermittency in such environments, not all data streams are delay-tolerant, and transmitting high-bandwidth DTN traffic over narrowband links can lead to significant inefficiencies. This paper presents QoS-MUWCom, a Quality of Service (QoS)-aware communication solution designed to manage both real-time and delay-tolerant traffic across dynamically selected multimodal interfaces. Experimental evaluations conducted in a freshwater tank demonstrate that QoS-MUWCom achieves near-zero packet loss for low-demand traffic even under link saturation, improves throughput for prioritized flows up to three times in mobility scenarios, and adapts to link availability and node mobility. The results confirm that QoS-MUWCom outperforms conventional multimodal strategies, contributing to more robust, resilient and efficient underwater communications.

Abstract
Force sensors are essential elements of actuator systems, providing measurement and force control in different domains. This literature review discusses its applications in the industry, academic research, and educational domains. In an industrial setup, force sensors enhance efficiency, safety, and reliability within automation systems, predominantly robotic arms and assembly lines. In the academic environment, using such sensors fosters innovation within robotics and biomechanical studies, allowing for testing theoretical models and new methodologies. In education, force sensors help students understand basic concepts about mechanics and robotics from practical work. Understanding this diverse application allows one to design effective actuator systems, promoting technological advances and improved learning experiences. With this literary review, the aim is to gain an understanding of the state of the art in force sensor actuators applied in various areas, such as academia, education, and industry.

Abstract
We address the layout optimization problem of deciding the number, the location, and the operational space of a set of Airborne Wind Energy (AWE) units, which overall constitute an AWE farm. The layout optimization problem in conventional wind farms, with standard wind turbines, is a well-studied subject; however, in the case of AWE, there are several new characteristics and challenges. While in the case of conventional wind farms, the main concern is to guarantee a reduced aerodynamical wake effect from other units, in AWE the main concern is to avoid collision among units. The optimization problem addressed is the following: given a specific land dimension and local wind characteristics, we solve a bi-objective problem of maximizing power production while minimizing the number of units, by deciding the number of producing units, their locations, as well as their flight envelopes. The solution method uses a combination of metaheuristic methods, including elements from the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) and the Biased Random Key Genetic Algorithm (BRKGA). The results produce a custom Pareto set adapted to the wind local characteristics, allowing for a more accurate estimation of the key objectives, better estimate of the annual power output of the AWE farm, and make better-informed decisions regarding the optimal number of units to deploy in the farm.

Abstract
This study investigates the fabrication of plasmonic optical fiber sensors for glyphosate detection, employing silver thin film coatings deposited via the Tollens' reaction and further enhanced with protective gold plating. Silver films were produced through electroless deposition, forming rough plasmonic surfaces with localized hotspots that amplify the electromagnetic field. Surface roughness effects on the creation of hotspots were first evaluated numerically using the finite element method (FEM) and later experimentally assessed the impact on optical response. Furthermore, to address the inherent susceptibility of silver to oxidation and corrosion, a gold plating was applied using the Kirkendall effect, selectively replacing surface silver atoms with gold. This approach significantly improved the chemical stability of the sensors while preserving their plasmonic properties. This configuration was applied in developing a biosensor, using aptamers, for detecting glyphosate in concentrations ranging from 10(-1) to 10(4) mu g/L. The results demonstrated a sensitivity of 25.08 +/- 0.22 nm/(mu g/L) and a limit of detection (LOD) of 0.04 mu g/L, nearly ten times lower than the European Union's safety limit for glyphosate. Experimental results highlight the potential of this fabrication approach for developing sensitive, stable, and scalable plasmonic sensors tailored for environmental and agricultural monitoring applications.