Abstract
Fire is a traditional method used for the elimination of residual materials from agricultural and forestry activities, but its improper and negligent use increases the risk to cause significant social, economic, and environmental impacts. Translating the nature and magnitude of the risk, a mental model approach has been used for a deeper understanding of what can be done to reduce future socioeconomic and environmental impacts. Considering the rural fire risk context, in this study we applied the mental model approach to (1) explore the different perspectives of experts on rural fire risks, focusing on the burning problem, and (2) systematize the aggregated knowledge of experts on the subject. Semi-structured interviews that included real-time interactions with the proposed mental model on the MURAL platform were remotely conducted with twenty-eight experts with in-depth involvement and experience in fire and forest management in Portugal, including actors from industry, academics, third sector, and public entities. The experts' contributions were periodically validated by the research team and included in the reference mental model to translate the aggregated knowledge of the expert community. The data collected was transcribed, coded, and analyzed following a thematic analysis approach with NVivo software support. After nine iterations, the expert's mental model was concluded encompassing the burning motivators, alternative solutions, associated risks before and during the burning, underlying causes, natural elements and factors, and impacts. Overall, the study provides an in-depth and holistic understanding of rural fire risks, focusing on burning, which is essential for identifying incorrect beliefs and existing risk factors that are often neglected. The participatory and dynamic process of actors' knowledge systematization on burning risks through a mental model allowed the identification of divergent perspectives between expert groups, especially concerning the effectiveness of the current legislation on the use of fire, indicating the need to improve the dialogue between experts. Moreover, the study shows how risk communication campaigns do not replace technical monitoring closer to the population and recognize the importance and need of sensitization and communication actions to disseminate the use of available alternatives to overcome traditional habits of rural communities. Still, it indicates that successful alternative solutions of burning may be achieved with strong local and sectoral involvement. Finally, this research provides a baseline to help decision-makers and stakeholders identify the most relevant variables about rural fire risks to build effective risk communications strategies and mitigate social and environmental impacts in the future.

Abstract
Climate change increases the average temperature and reduces precipitation, leading to an increased risk of rural fires around the world, but mainly in regions with a Mediterranean climate, such as Portugal. Despite the high risk of rural fires, fire is still a traditional land management practice. Beyond fire misused risk, the accumulation of fuel loads, due to the high population dispersion and lower interaction of communities with the land, also drives rural fires risks. Thus, researchers have sought to understand the key features of communication practices to achieve the most desired natural risk management results in relation to rural fires. According to the Committee on Risk Perception and Communication, in 1989, risk communication is defined as “an interactive process of exchanging information and opinions between individuals, groups, and institutions�. However, there is a need for dialogue between the responsible for communication and relevant stakeholders. The Carnegie Mellon mental-models approach encompasses participatory processes to translate the nature and magnitude of the risk, allowing for a deeper understanding of what can be done to mitigate social and environmental impacts in the future. Considering rural fires risks and risk communication challenges, this study aims to design an effective risk communication plan oriented to the rural population, in the context of rural fires. For this objective to be achieved, the mental models approach was developed, exploring the underlying reasons for resistance to behavioral change and defining guidelines to support the design of new risk communication strategies, including the dissemination of new behaviors and practices that mitigate the ignition of rural fires. This systemic approach has been applied and tested in the rePLANT project, whose purpose is the development of research activities, innovation and transfer of knowledge and technology, to increase sustainable forest management, the competitiveness of the Portuguese forestry sector and reduce the impact of rural fires. Preliminary findings show what must be communicated about rural fires risk, how must be communicated, target audiences' profiles, the role of actors for effective risk communication on rural fires, attributes of good risk communication on rural fires, evaluation of the risk communication results. Finally, it is expected that this research provides guidelines to help decision-makers and stakeholders to design an effective risk communication plan oriented to prevent traditional burning practices, as well as to mitigate socioeconomic and environmental impacts in the future. This approach also highlights the importance of exploring the underlying reasons for resistance to behavioral change and defining guidelines to support the design of new risk communication strategies.

Abstract
[No abstract available]

Abstract
Firms have available many forms of collaboration, including cooperatives or joint ventures, in this way leveraging their market power. Customers, however, are atomic agents with few mechanisms for collaborating, leading to an unbalanced buyer-supplier relationship and economic surpluses that shift to producers. Some group buying websites helped alleviate the problem by offering bulk discounts, but more advancements can be made with the emergence of technologies, such as the blockchain. In this article, we propose a customer-push e-marketplace built on top of Ethereum, where customers can aggregate their proposals, and suppliers try to outcompete each other in reverse auction bids to fulfil the order. Furthermore, smart contracts make it possible to automate many operational activities, such as payment escrows/release upon delivery confirmation, increasing the efficiency along the supply chain. The implementation of this network is expected to improve market efficiency by reducing transaction costs, time delays, and information asymmetry. Furthermore, concepts such as increased bargaining power and economies of scale, and their effects in buyer-supplier relationships, are also explored.

Abstract
Sectorization problems have significant challenges arising from the many objectives that must be optimised simultaneously. Several methods exist to deal with these many-objective optimisation problems, but each has its limitations. This paper analyses an application of Preference Inspired Co-Evolutionary Algorithms, with goal vectors (PICEA-g) to sectorization problems. The method is tested on instances of different size difficulty levels and various configurations for mutation rate and population number. The main purpose is to find the best configuration for PICEA-g to solve sectorization problems. Performance metrics are used to evaluate these configurations regarding the solutions’ spread, convergence, and diversity in the solution space. Several test trials showed that big and medium-sized instances perform better with low mutation rates and large population sizes. The opposite is valid for the small size instances. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The CrossLog project aims to investigate, study, develop and implement an automated and collaborative cross-docking system (aligned with Industry 4.0) capable of moving and managing the flow of products within the warehouse in the fastest and safest way. In CrossLog, the ability to generate intelligent three-dimensional packing patterns is essential to ensure the flexibility and productivity of the cross-docking system while ensuring the stability of the palletised load. In this work, a heuristic solution approach is proposed to generate efficient pallet packing patterns that simultaneously minimise the total number of pallets required and address the balance of weight and volume between pallets. Computational experiments with data from a real company demonstrate the quality of the proposed solution approach.