Abstract
This paper investigates the stability of a converter-dominated islanded power system when the island’s battery energy storage converters are operated in different control modes (Grid Forming and Grid Following) and combined with different volumes of synchronous compensation. The study is conducted in a realistic simulation model of the future Madeira island, where no thermal generation is present, and the share of converter-based Renewable Energy Sources is large (75 to 80 % of instantaneous penetration). The impact of the different combinations of synchronous condensers and BESS converter control modes on the system stability is evaluated using a stability index-based approach that accounts for multiple operation scenarios. In this procedure, the system’s dynamic response to the reference disturbances (short-circuits in the Transmission and Distribution Network) is obtained via RMS dynamic simulation and is then analyzed to extract two stability indices (Nadir and Rocof). Such indices are computed for the synchronous generator speed and the grid electrical frequency (measured in different points using a PLL) and are later used as the basis for discussion and conclusion drawing. © Energynautics GmbH.

Abstract
The paper presents the comparison of accuracy in the Speech Emotion Recognition task using the Hamming and Hanning windows for framing the speech and determining the spectrogram to be used as input of a convolutional neural network. The detection of between 4 and 10 emotional states was tested for both windows. The results show significant differences in accuracy between the two window types and provide valuable insights for the development of more efficient emotional state detection systems. The best accuracy between 4 and 10 emotions was 64.1% (4 emotions), 57.8% (5 emotions), 59.8% (6 emotions), 48.4% (7 emotions), 47.8% (8 emotions), 51.4% (9 emotions), and 45.9% (10 emotions). These accuracy is at the state-of-the art level.

Abstract
The transition to college is a period of higher risk of the development of eating disorders, with nutrition/dietetics students representing a group of particular vulnerability. Hence, it is interesting to assess eating disorders, taking into consideration potential sources of bias, including social desirability. Our aims were to compare the risk of eating disorders between students of nutrition/dietetics and those attending other courses and to study potential social desirability biases. A total of 799 higher education students (81.7% females) aged 18 to 27 years old completed a questionnaire assessing the risk of eating disorders (EAT-26) and social desirability (composite version of the Marlowe-Crowne Social Desirability Scale). The proportion of students with a high risk of eating disorders was higher among females (14.5% vs. 8.2%, p = 0.044). Nutrition/dietetics students did not differ from those attending other courses regarding the risk of eating disorders. The social desirability bias when assessing the risk of eating disorders was overall low (EAT-26 total score: r = -0.080, p = 0.024). Social desirability correlated negatively with the Diet (r = -0.129, p < 0.001) and Bulimia and food preoccupation subscales (r = -0.180, p < 0.001) and positively with Oral self-control (r = 0.139, p < 0.001).

Abstract
During the process of software architectural design, numerous questions arise which must be answered. These questions may be about requirements on the proposed system (the problem space) or about how the system should be designed and developed (the solution space). As questions arise they may be answered immediately, deferred until later, or provisionally answered with an assumption about the answer. The objective of this work was to explore the nature of questions that arise during architecture. We explored the types of questions, how they are organized, how they are tracked, and how and when they are answered. We started by surveying highly experienced architects about their practices with respect to architectural questions. We also performed a controlled experiment with master students about organizing architectural questions that clarified and substantiated the survey data. We learned that architectural questions include slightly more questions about the problem space than the solution space, as well as a minority of questions related to the managing of the project. We found that architects often use ad hoc methods to organize and track them, although they typically organize them along more than one dimension. We learned also that, about a third of the time, architects make assumptions about the answers to architectural questions in order to make progress on the architecture. This suggests that some projects may have risks of incorrect design or later costly rework due to inadequate tracking or incorrectly answered architectural questions.

Abstract
The footwear industry is known for its longstanding traditional production methods that require intense manual labor. Roughing, for example, is regarded as one of the significant and critical operations in shoe manufacturing and consists of using abrasive tools to remove a thin layer of the shoe's surface, creating a slightly roughened texture that provides a better surface area for adhesion. As such, workers are typically subjected to hazardous substances (i.e., dust, chromium), repetitive strain injuries, and ergonomic challenges. Although robots can automate repetitive tasks and perform with high precision and consistency, the footwear industry is usually reluctant to employ industrial robots due to the need for restructuring. This paper addresses the challenge of re-designing the lateral roughing of uppers to allow robot-assisted manufacturing with minimal modifications in the manufacturing process. The proposed innovative system employs a robotic manipulator to perform roughing based on data collected from preceding manufacturing steps. Workers marking the mesh line of each sole-upper pair can simultaneously teach the manipulator path for that same pair, using a programming-by-demonstration approach. Multiple paths were collected by outlining a piece of footwear, converted into robot instructions, and deployed on a simulated and real industrial manipulator. The key findings of this research showcase the capability of the proposed solution to replicate collected paths accurately, indicating potential applications not only in roughing processes but also in similar tasks like primer and adhesive application.

Abstract
This paper proposes an original framework for a flexibility-centric value chain and describes the pre-specification of the Grid Data and Business Network (GDBN), a digital platform to provide support to the flexibility value chain activities. First, it outlines the structure of the value chain with the most important tasks and actors in each activity. Next, it describes the GDBN concept, including stakeholders' engagement and conceptual architecture. It presents the main GDBN services to support the flexibility value chain, including, matching consumers and assets and service providers, assets installation and operationalization to provide flexibility, services for energy communities and services, for consumers, aggregators, and distribution systems operators, to participate in flexibility markets. At last, it details the workflow and life cycle management of this platform and discusses candidate business models that could support its implementation in real-life scenarios.