Abstract
Choreographic languages describe possible sequences of interactions among a set of agents. Typical models are based on languages or automata over sending and receiving actions. Pomsets provide a more compact alternative by using a partial order to explicitly represent causality and concurrency between these actions. However, pomsets offer no representation of choices, thus a set of pomsets is required to represent branching behaviour. For example, if an agent Alice can send one of two possible messages to Bob three times, one would need a set of 2 x 2 x 2 distinct pomsets to represent all possible branches of Alice's behaviour. This paper proposes an extension of pomsets, named branching pomsets, with a branching structure that can represent Alice's behaviour using 2 + 2 + 2 ordered actions. We compare the expressiveness of branching pomsets with that of several forms of event structures from the literature. We encode choreographies as branching pomsets and show that the pomset semantics of the encoded choreographies are bisimilar to their operational semantics. Furthermore, we define well-formedness conditions on branching pomsets, inspired by multiparty session types, and we prove that the well-formedness of a branching pomset is a sufficient condition for the realisability of the represented com-munication protocol. Finally, we present a prototype tool that implements our theory of branching pomsets, focusing on its applications to choreographies. (c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/).

Abstract
There is no doubt that tourism benefits Portugal's economy. The area should be able to better target the market for its travel and tourist products and increase its performance with the use of a marketing strategy, especially in a field where global competition is always increasing. This digital marketing plan seeks to analyze the strengths and limitations of the Portuguese region in its target markets, as well as the most current advancements in the global travel and tourism sector. In this work, it is conducted an analysis of both micro and macro environments of Casa Pereirinha. In addition, it was created a marketing mix based on the 7P's. Furthermore, the work provides the prospective avenues for product growth and marketing following the markets' stated growth objectives. This project comprises creating a comprehensive digital marketing strategy for Casa Pereirinha as a significant example of the region's tourism business, and the primary purpose is to conserve its past, while developing a new strategy.

Abstract
Sustainable agri-food systems seek to deliver food affordably and sustainably, without compromising the economic, social, and environmental bases for current and coming generations. Food-energy systems integrating renewable energy sources contribute towards this sustainability, and new solutions are being proposed in the literature or implemented in real facilities. This work reviews the existing literature on the integration of renewable energy, cross-sector energy efficiency and flexibility approaches, circular economy, digital solutions, and energy communities' (EC) structures within the agri-food sector. It proposes a formal classification of the main solutions found and describes the associated Business Models (BMs) to support their actual development cost-effectively. The main roles, actors and value propositions are reviewed, and a case example of an EC to be developed in Portugal in the Tools4AgriEnergy project is also described. The EC is based on floating PV panels to power water distribution pumps and share the surplus with local agri-food industries.

Abstract
Entrepreneurs’ decision-making in sustainable open innovation practices holds significant relevance in fostering environmentally conscious and socially responsible business strategies. Sustainable decision-making not only aligns with ethical principles but also addresses pressing global challenges such as climate change and resource depletion. This study aims to characterize the decision-making role played by entrepreneurs in the context of the open innovation paradigm and to understand the factors that influence entrepreneurial performance. A quantitative methodology supported by Partial Least Squares Structural Equation Modeling was adopted, considering a sample of 407 startups incubated in science and technology parks. After that, a mixed-methods approach was employed to explore the differences between sectors of activity, in which 4 ventures were involved. The results confirm that of the 9 hypotheses formulated in the relationship between the constructs, only innovation novelty is not significant for sustainable open innovation management processes, unlike innovation openness. This study offers theoretical and practical implications for startups that intend to use open innovation networks to integrate environmental and social considerations into the core of business strategies.

Abstract
Integrating Industry 4.0 and Quality 4.0 optimises manufacturing through IoT and ML, improving processes and product quality. The primary challenge involves identifying patterns in computer numerical control (CNC) machining time-series data to boost manufacturing quality control. The proposed solution involves an experimental study comparing one-class and binary classification algorithms. This study aims to classify time-series data from CNC turning machines, offering insight into monitoring and adjusting tool wear to maintain product quality. The methodology entails extracting spectral features from time-series data to train both one-class and binary classification algorithms, assessing their effectiveness and computational efficiency. Although certain models consistently outperform others, determining the best performing is not possible, as a trade-off between classification and computational performance is observed, with gradient boosting standing out for effectively balancing both aspects. Thus, the choice between one-class and binary classification ultimately relies on dataset's features and task objectives.

Abstract
This study provides a comprehensive overview of the automated assembly process of large-scale metal structures using industrial robots. Our research reveals that the utilization of industrial robots significantly enhances precision, speed, and cost-effectiveness in the assembly process. The main findings suggest that integrating industrial robots in metal structure assembly holds substantial promise for optimizing manufacturing processes and elevating the quality of the final products. Additionally, the research demonstrates that robotic automation in assembly operations can lead to significant improvements in resource utilization and operational consistency. This automation also offers a viable solution to the challenges of manual labor shortages and ensures a higher standard of safety and accuracy in the manufacturing environment.