Abstract
This paper investigates the contribution of hydrogen electrolysers (HEs) for frequency related Ancillary Services (AS), namely Frequency Containment Reserve (FCR), Synthetic Inertia (SI) , Fast Frequency Response (FFR) in future operation scenarios in the Iberian Peninsula (IP) considering low system iner-tia. The proposed framework for analysis consists of a dynamic model developed in MATLAB/Simulink. Simulations show that an instantaneous inverter based resource (IBR) trip induced by a grid fault may lead to the occurrence of values of Rate of Change of Frequency (RoCoF) close to undesirable thresholds if the FCR is provided solely by the conventional generators. The obtained results illustrate that HEs can outperform conventional generators on the provision of FCR. Furthermore, the FCR is unable to unlock the full potential of fast responding HEs. This suggests the advantage of providing additional AS such as SI or FFR in critical periods. Simulations also show that the benefit of additional AS can be limited in specific conditions, especially depending on the evolution of HEs' ramping capabilities, but are still a relevant complement to other solutions designed to deal with low inertia in power systems such as synchronous compensators.& COPY; 2023 Elsevier Ltd. All rights reserved.

Abstract
The use of Unmanned Aerial Vehicles (UAVs) in different inspection tasks is increasing. This technology reduces inspection costs and collects high quality data of distinct structures, including areas that are not easily accessible by human operators. However, the reduced energy available on the UAVs limits their flight endurance. To increase the autonomy of a single flight, it is important to optimize the path to be performed by the UAV, in terms of energy loss. Therefore, this work presents a novel formulation of the Travelling Salesman Problem (TSP) and a path planning algorithm that uses a UAV energy model to solve this optimization problem. The novel TSP formulation is defined as Asymmetric Travelling Salesman Problem with Precedence Loss (ATSP-PL), where the cost of moving the UAV depends on the previous position. The energy model relates each UAV movement with its energy consumption, while the path planning algorithm is focused on minimizing the energy loss of the UAV, ensuring that the structure is fully covered. The developed algorithm was tested in both simulated and real scenarios. The simulated experiments were performed with realistic models of wind turbines and a UAV, whereas the real experiments were performed with a real UAV and an illumination tower. The inspection paths generated presented improvements over 24% and 8%, when compared with other methods, for the simulated and real experiments, respectively, optimizing the energy consumption of the UAV.

Abstract

Abstract
Occupational safety is a major concern these days because it is an important social issue promoting financial implications for organisations, employees, and society. But while occupational safety is an important concern, the top management of organizations usually prioritize waste and cost reduction. Therefore, there is a need for a technique that reduces waste and simultaneously improves occupational safety. Lean has been effective in reducing waste and costs. Some researchers have shown that Lean can also improve occupational safety. The objective of this work was to determine wether, in organizations where Lean tools were implemented, if there was an improvement in occupational safety conditions, namely in the reduction of accident rates, and to verify which Lean tools contributed the most to that improvement. A survey was conducted by sending a questionnaire to Portuguese organizations, from north to south and islands, who had potentially Lean tools implemented. In total, 189 answers have been obtained from organizations, 59 of which had Lean tools implemented, being considered valid answers for the study. Through statistical analysis of the data obtained, it was found that no organisations had worsened their safety indicators, some had maintained the same level and a reasonable number stated that their indicators had improved. Of these, the vast majority said that their accident rates had decreased by 20%, this being the figure that statistically showed the best results in terms of change.

Abstract
A sensor based on a balloon-like interferometer and a spring-shaped structure for micro curvature measurement is proposed and experimentally demonstrated. The sensor is composed by singlemode fiber inserted into a capillary tube. The experimental results show micro-curvature sensitivities of -35.04 pm/mu m, -28.07 pm/mu m e -18.7 pm/mu m in the range from 0 to 200 mu m for three resonants dips lambda(1), lambda(2) and lambda(3), respectively. In addition, the sensor has advantages of easy fabrication, low cost, and satisfactory sensitivity, which shows good results of sensing of micro curvature in some applications.

Abstract
Machine learning methods to aid defence systems in detecting malicious activity typically rely on labelled data. In some domains, such labelled data is unavailable or incomplete. In practice this can lead to low detection rates and high false positive rates, which characterise for example anti-money laundering systems. In fact, it is estimated that 1.7-4 trillion euros are laundered annually and go undetected. We propose The GANfather, a method to generate samples with properties of malicious activity, without label requirements. We propose to reward the generation of malicious samples by introducing an extra objective to the typical Generative Adversarial Networks (GANs) loss. Ultimately, our goal is to enhance the detection of illicit activity using the discriminator network as a novel and robust defence system. Optionally, we may encourage the generator to bypass pre-existing detection systems. This setup then reveals defensive weaknesses for the discriminator to correct. We evaluate our method in two real-world use cases, money laundering and recommendation systems. In the former, our method moves cumulative amounts close to 350 thousand dollars through a network of accounts without being detected by an existing system. In the latter, we recommend the target item to a broad user base with as few as 30 synthetic attackers. In both cases, we train a new defence system to capture the synthetic attacks.